Overview

Dataset statistics

Number of variables67
Number of observations78
Missing cells839
Missing cells (%)16.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory41.0 KiB
Average record size in memory537.6 B

Variable types

Categorical67

Alerts

Time has a high cardinality: 75 distinct values High cardinality
Decimal has a high cardinality: 72 distinct values High cardinality
Illumination level (Lux) has a high cardinality: 75 distinct values High cardinality
Color Tempreture has a high cardinality: 74 distinct values High cardinality
Average Noise level has a high cardinality: 74 distinct values High cardinality
O2 Concentration (%Vol) has a high cardinality: 66 distinct values High cardinality
CO2 at any moment (PPM) has a high cardinality: 75 distinct values High cardinality
LPG concen (ppm) has a high cardinality: 73 distinct values High cardinality
Methan Concen (ppm) has a high cardinality: 70 distinct values High cardinality
CO concen (ppm) has a high cardinality: 71 distinct values High cardinality
Hydrogyn Concen (ppm) has a high cardinality: 72 distinct values High cardinality
Netric tVOC level (ppm) has a high cardinality: 69 distinct values High cardinality
VOC Formerdahied Level (ppm) has a high cardinality: 69 distinct values High cardinality
Different VOC (CO) Level (ppm) has a high cardinality: 63 distinct values High cardinality
Room Temp ( C ) has a high cardinality: 73 distinct values High cardinality
Room reative humadity % has a high cardinality: 72 distinct values High cardinality
Radiant Temp 1 (C).1 has a high cardinality: 63 distinct values High cardinality
Wind Speed (mm/s) has a high cardinality: 53 distinct values High cardinality
Timestamp has a high cardinality: 72 distinct values High cardinality
In average day how much time do you spend in the [Office ] is highly correlated with In average day how much time do you spend in the [laboratory ] and 26 other fieldsHigh correlation
Hydrogyn Concen (ppm) is highly correlated with CO2 at any moment (PPM) and 18 other fieldsHigh correlation
In average day how much time do you spend in the [laboratory ] is highly correlated with In average day how much time do you spend in the [Office ] and 30 other fieldsHigh correlation
Occupation is highly correlated with In average day how much time do you spend in the [Office ] and 41 other fieldsHigh correlation
Does the quality of air in this part of building have a negative effect on your work performance "most time feeling"? is highly correlated with Occupation and 27 other fieldsHigh correlation
CO2 at any moment (PPM) is highly correlated with Hydrogyn Concen (ppm) and 38 other fieldsHigh correlation
CO concen (ppm) is highly correlated with Hydrogyn Concen (ppm) and 17 other fieldsHigh correlation
Different VOC (CO) Level (ppm) is highly correlated with Hydrogyn Concen (ppm) and 17 other fieldsHigh correlation
Room Temp ( C ) is highly correlated with Hydrogyn Concen (ppm) and 27 other fieldsHigh correlation
How would you describe the summer indoor air temperature "most time feeling"? is highly correlated with In average day how much time do you spend in the [Office ] and 31 other fieldsHigh correlation
Do you have control over artificial lightning ? is highly correlated with In average day how much time do you spend in the [Office ] and 44 other fieldsHigh correlation
Unnamed: 61 is highly correlated with In average day how much time do you spend in the [laboratory ] and 41 other fieldsHigh correlation
How long have you (worked-studied) in this building is highly correlated with In average day how much time do you spend in the [Office ] and 24 other fieldsHigh correlation
How would you describe the noise in building generally "most time feeling"? is highly correlated with In average day how much time do you spend in the [Office ] and 33 other fieldsHigh correlation
Decimal is highly correlated with Hydrogyn Concen (ppm) and 38 other fieldsHigh correlation
Height is highly correlated with Occupation and 18 other fieldsHigh correlation
Radiant Temp 2 (C) is highly correlated with CO2 at any moment (PPM) and 13 other fieldsHigh correlation
Do you smell odor or unusual smell in your work-space "most time feeling"? is highly correlated with In average day how much time do you spend in the [Office ] and 41 other fieldsHigh correlation
Color Tempreture is highly correlated with Hydrogyn Concen (ppm) and 26 other fieldsHigh correlation
LPG concen (ppm) is highly correlated with Hydrogyn Concen (ppm) and 18 other fieldsHigh correlation
Unnamed: 64 is highly correlated with Occupation and 31 other fieldsHigh correlation
Room name and code is highly correlated with In average day how much time do you spend in the [Office ] and 20 other fieldsHigh correlation
Does the temperature in this part of the building have a negative effect on your work performance? is highly correlated with In average day how much time do you spend in the [Office ] and 38 other fieldsHigh correlation
Do you feel comfortable under the current temperature ? is highly correlated with In average day how much time do you spend in the [laboratory ] and 22 other fieldsHigh correlation
Is there significant distraction from noise outside (in this moment) ? is highly correlated with In average day how much time do you spend in the [Office ] and 37 other fieldsHigh correlation
Illumination level (Lux) is highly correlated with Hydrogyn Concen (ppm) and 38 other fieldsHigh correlation
Does the quality of light (color and light level) in this part of building have a negative effect on your work performance ? is highly correlated with In average day how much time do you spend in the [laboratory ] and 26 other fieldsHigh correlation
Alcohole Concen (ppm) is highly correlated with Hydrogyn Concen (ppm) and 12 other fieldsHigh correlation
Age is highly correlated with In average day how much time do you spend in the [Office ] and 43 other fieldsHigh correlation
Unnamed: 63 is highly correlated with In average day how much time do you spend in the [Office ] and 38 other fieldsHigh correlation
Room reative humadity % is highly correlated with CO2 at any moment (PPM) and 14 other fieldsHigh correlation
How would describe noise at this moment? is highly correlated with Does the quality of air in this part of building have a negative effect on your work performance "most time feeling"? and 28 other fieldsHigh correlation
How would you describe the ventilation and air quality of building "most time feeling"? is highly correlated with Occupation and 23 other fieldsHigh correlation
In average day how much time do you spend working at computer "average hours per day" is highly correlated with In average day how much time do you spend in the [Office ] and 18 other fieldsHigh correlation
Time is highly correlated with Hydrogyn Concen (ppm) and 38 other fieldsHigh correlation
How you describe the current temperature in this room? is highly correlated with In average day how much time do you spend in the [Office ] and 30 other fieldsHigh correlation
Unnamed: 65 is highly correlated with In average day how much time do you spend in the [Office ] and 41 other fieldsHigh correlation
Is there availability of natural light? is highly correlated with In average day how much time do you spend in the [laboratory ] and 23 other fieldsHigh correlation
Netric tVOC level (ppm) is highly correlated with Hydrogyn Concen (ppm) and 18 other fieldsHigh correlation
Radiant Temp 3 (C) is highly correlated with Hydrogyn Concen (ppm) and 15 other fieldsHigh correlation
Clothing is highly correlated with In average day how much time do you spend in the [Office ] and 13 other fieldsHigh correlation
Unnamed: 62 is highly correlated with Occupation and 38 other fieldsHigh correlation
Do you have control over air condition system ? is highly correlated with In average day how much time do you spend in the [Office ] and 44 other fieldsHigh correlation
Radiant Temp 1 (C) is highly correlated with Hydrogyn Concen (ppm) and 13 other fieldsHigh correlation
In average day how much time do you spend in the [Studio Design] is highly correlated with In average day how much time do you spend in the [Office ] and 25 other fieldsHigh correlation
Does the distraction from noise in this part of building have a negative effect on your work performance "most time feeling"? is highly correlated with In average day how much time do you spend in the [Office ] and 35 other fieldsHigh correlation
In average day how much time do you spend in the [Cafeteria ] is highly correlated with In average day how much time do you spend in the [Office ] and 35 other fieldsHigh correlation
Location is highly correlated with Occupation and 11 other fieldsHigh correlation
In average day how much time do you spend in the [Lecture room ] is highly correlated with In average day how much time do you spend in the [Office ] and 30 other fieldsHigh correlation
Are there blinds or shutters blocking the natural light ? is highly correlated with In average day how much time do you spend in the [Office ] and 46 other fieldsHigh correlation
Unnamed: 66 is highly correlated with In average day how much time do you spend in the [laboratory ] and 40 other fieldsHigh correlation
Is there any luminare is OFF at this moment? is highly correlated with Occupation and 28 other fieldsHigh correlation
How long do you spend in the building during the day is highly correlated with In average day how much time do you spend in the [Office ] and 27 other fieldsHigh correlation
Gender is highly correlated with In average day how much time do you spend in the [Office ] and 47 other fieldsHigh correlation
Average Noise level is highly correlated with Hydrogyn Concen (ppm) and 25 other fieldsHigh correlation
How would you describe the winter indoor air temperature "most time feeling" is highly correlated with In average day how much time do you spend in the [Office ] and 31 other fieldsHigh correlation
Your Activity is highly correlated with In average day how much time do you spend in the [laboratory ] and 23 other fieldsHigh correlation
Do you feel sleepy or headache when you get to your work-space "most time feeling"? is highly correlated with Occupation and 27 other fieldsHigh correlation
Wind Speed (mm/s) is highly correlated with Hydrogyn Concen (ppm) and 16 other fieldsHigh correlation
Weight is highly correlated with In average day how much time do you spend in the [Office ] and 25 other fieldsHigh correlation
Right now, do you smell unusual smell? is highly correlated with Does the quality of air in this part of building have a negative effect on your work performance "most time feeling"? and 22 other fieldsHigh correlation
Methan Concen (ppm) is highly correlated with Hydrogyn Concen (ppm) and 16 other fieldsHigh correlation
O2 Concentration (%Vol) is highly correlated with Hydrogyn Concen (ppm) and 9 other fieldsHigh correlation
Radiant Temp 1 (C).1 is highly correlated with Hydrogyn Concen (ppm) and 15 other fieldsHigh correlation
VOC Formerdahied Level (ppm) is highly correlated with Hydrogyn Concen (ppm) and 16 other fieldsHigh correlation
Is there significant distraction from background noise (machine and undefined noise sources)? is highly correlated with In average day how much time do you spend in the [Office ] and 28 other fieldsHigh correlation
Location is highly correlated with Time and 61 other fieldsHigh correlation
Time is highly correlated with Location and 44 other fieldsHigh correlation
Decimal is highly correlated with Location and 44 other fieldsHigh correlation
Illumination level (Lux) is highly correlated with Location and 44 other fieldsHigh correlation
Color Tempreture is highly correlated with Location and 44 other fieldsHigh correlation
Average Noise level is highly correlated with Location and 42 other fieldsHigh correlation
O2 Concentration (%Vol) is highly correlated with Location and 42 other fieldsHigh correlation
CO2 at any moment (PPM) is highly correlated with Location and 44 other fieldsHigh correlation
LPG concen (ppm) is highly correlated with Location and 43 other fieldsHigh correlation
Alcohole Concen (ppm) is highly correlated with Location and 62 other fieldsHigh correlation
Methan Concen (ppm) is highly correlated with Location and 40 other fieldsHigh correlation
CO concen (ppm) is highly correlated with Location and 41 other fieldsHigh correlation
Hydrogyn Concen (ppm) is highly correlated with Location and 44 other fieldsHigh correlation
Netric tVOC level (ppm) is highly correlated with Location and 40 other fieldsHigh correlation
VOC Formerdahied Level (ppm) is highly correlated with Location and 41 other fieldsHigh correlation
Different VOC (CO) Level (ppm) is highly correlated with Location and 42 other fieldsHigh correlation
Room Temp ( C ) is highly correlated with Location and 44 other fieldsHigh correlation
Room reative humadity % is highly correlated with Location and 44 other fieldsHigh correlation
Radiant Temp 1 (C) is highly correlated with Time and 51 other fieldsHigh correlation
Radiant Temp 2 (C) is highly correlated with Location and 49 other fieldsHigh correlation
Radiant Temp 3 (C) is highly correlated with Time and 46 other fieldsHigh correlation
Radiant Temp 1 (C).1 is highly correlated with Location and 43 other fieldsHigh correlation
Wind Speed (mm/s) is highly correlated with Location and 47 other fieldsHigh correlation
Timestamp is highly correlated with Location and 59 other fieldsHigh correlation
Room name and code is highly correlated with Location and 47 other fieldsHigh correlation
Gender is highly correlated with Location and 65 other fieldsHigh correlation
Occupation is highly correlated with Location and 63 other fieldsHigh correlation
Age is highly correlated with Location and 62 other fieldsHigh correlation
Height is highly correlated with Time and 60 other fieldsHigh correlation
Weight is highly correlated with Location and 45 other fieldsHigh correlation
Your Activity is highly correlated with Location and 46 other fieldsHigh correlation
Clothing is highly correlated with Alcohole Concen (ppm) and 45 other fieldsHigh correlation
How long do you spend in the building during the day is highly correlated with Location and 45 other fieldsHigh correlation
How long have you (worked-studied) in this building is highly correlated with Location and 44 other fieldsHigh correlation
In average day how much time do you spend in the [Office ] is highly correlated with Location and 45 other fieldsHigh correlation
In average day how much time do you spend in the [Lecture room ] is highly correlated with Location and 46 other fieldsHigh correlation
In average day how much time do you spend in the [laboratory ] is highly correlated with Location and 47 other fieldsHigh correlation
In average day how much time do you spend in the [Studio Design] is highly correlated with Location and 44 other fieldsHigh correlation
In average day how much time do you spend in the [Cafeteria ] is highly correlated with Location and 46 other fieldsHigh correlation
In average day how much time do you spend working at computer "average hours per day" is highly correlated with Location and 46 other fieldsHigh correlation
Does the temperature in this part of the building have a negative effect on your work performance? is highly correlated with Location and 44 other fieldsHigh correlation
How would you describe the summer indoor air temperature "most time feeling"? is highly correlated with Location and 44 other fieldsHigh correlation
How would you describe the winter indoor air temperature "most time feeling" is highly correlated with Location and 45 other fieldsHigh correlation
Do you feel comfortable under the current temperature ? is highly correlated with Location and 44 other fieldsHigh correlation
How you describe the current temperature in this room? is highly correlated with Location and 44 other fieldsHigh correlation
Does the distraction from noise in this part of building have a negative effect on your work performance "most time feeling"? is highly correlated with Location and 48 other fieldsHigh correlation
Is there significant distraction from noise outside (in this moment) ? is highly correlated with Location and 48 other fieldsHigh correlation
Is there significant distraction from background noise (machine and undefined noise sources)? is highly correlated with Location and 43 other fieldsHigh correlation
How would you describe the noise in building generally "most time feeling"? is highly correlated with Location and 44 other fieldsHigh correlation
How would describe noise at this moment? is highly correlated with Location and 64 other fieldsHigh correlation
Does the quality of air in this part of building have a negative effect on your work performance "most time feeling"? is highly correlated with Location and 60 other fieldsHigh correlation
Do you have control over air condition system ? is highly correlated with Location and 63 other fieldsHigh correlation
How would you describe the ventilation and air quality of building "most time feeling"? is highly correlated with Location and 64 other fieldsHigh correlation
Do you smell odor or unusual smell in your work-space "most time feeling"? is highly correlated with Location and 64 other fieldsHigh correlation
Do you feel sleepy or headache when you get to your work-space "most time feeling"? is highly correlated with Location and 65 other fieldsHigh correlation
Right now, do you smell unusual smell? is highly correlated with Location and 59 other fieldsHigh correlation
Does the quality of light (color and light level) in this part of building have a negative effect on your work performance ? is highly correlated with Location and 64 other fieldsHigh correlation
Is there availability of natural light? is highly correlated with Location and 65 other fieldsHigh correlation
Are there blinds or shutters blocking the natural light ? is highly correlated with Location and 65 other fieldsHigh correlation
Do you have control over artificial lightning ? is highly correlated with Location and 62 other fieldsHigh correlation
Is there any luminare is OFF at this moment? is highly correlated with Location and 57 other fieldsHigh correlation
Unnamed: 61 is highly correlated with Location and 62 other fieldsHigh correlation
Unnamed: 62 is highly correlated with Location and 65 other fieldsHigh correlation
Unnamed: 63 is highly correlated with Location and 65 other fieldsHigh correlation
Unnamed: 64 is highly correlated with Location and 62 other fieldsHigh correlation
Unnamed: 65 is highly correlated with Location and 65 other fieldsHigh correlation
Unnamed: 66 is highly correlated with Location and 65 other fieldsHigh correlation
Location has 2 (2.6%) missing values Missing
Time has 2 (2.6%) missing values Missing
Decimal has 5 (6.4%) missing values Missing
Illumination level (Lux) has 2 (2.6%) missing values Missing
Color Tempreture has 2 (2.6%) missing values Missing
Average Noise level has 2 (2.6%) missing values Missing
O2 Concentration (%Vol) has 2 (2.6%) missing values Missing
CO2 at any moment (PPM) has 2 (2.6%) missing values Missing
LPG concen (ppm) has 2 (2.6%) missing values Missing
Alcohole Concen (ppm) has 2 (2.6%) missing values Missing
Methan Concen (ppm) has 2 (2.6%) missing values Missing
CO concen (ppm) has 2 (2.6%) missing values Missing
Hydrogyn Concen (ppm) has 2 (2.6%) missing values Missing
Netric tVOC level (ppm) has 2 (2.6%) missing values Missing
VOC Formerdahied Level (ppm) has 2 (2.6%) missing values Missing
Different VOC (CO) Level (ppm) has 2 (2.6%) missing values Missing
Room Temp ( C ) has 2 (2.6%) missing values Missing
Room reative humadity % has 2 (2.6%) missing values Missing
Radiant Temp 1 (C) has 2 (2.6%) missing values Missing
Radiant Temp 2 (C) has 2 (2.6%) missing values Missing
Radiant Temp 3 (C) has 2 (2.6%) missing values Missing
Radiant Temp 1 (C).1 has 2 (2.6%) missing values Missing
Wind Speed (mm/s) has 2 (2.6%) missing values Missing
Timestamp has 2 (2.6%) missing values Missing
Room name and code has 2 (2.6%) missing values Missing
Gender has 2 (2.6%) missing values Missing
Occupation has 2 (2.6%) missing values Missing
Age has 2 (2.6%) missing values Missing
Height has 2 (2.6%) missing values Missing
Weight has 2 (2.6%) missing values Missing
Your Activity has 2 (2.6%) missing values Missing
Clothing has 2 (2.6%) missing values Missing
How long do you spend in the building during the day has 2 (2.6%) missing values Missing
How long have you (worked-studied) in this building has 2 (2.6%) missing values Missing
In average day how much time do you spend in the [Office ] has 2 (2.6%) missing values Missing
In average day how much time do you spend in the [Lecture room ] has 2 (2.6%) missing values Missing
In average day how much time do you spend in the [laboratory ] has 2 (2.6%) missing values Missing
In average day how much time do you spend in the [Studio Design] has 2 (2.6%) missing values Missing
In average day how much time do you spend in the [Cafeteria ] has 2 (2.6%) missing values Missing
In average day how much time do you spend working at computer "average hours per day" has 2 (2.6%) missing values Missing
Does the temperature in this part of the building have a negative effect on your work performance? has 2 (2.6%) missing values Missing
How would you describe the summer indoor air temperature "most time feeling"? has 2 (2.6%) missing values Missing
How would you describe the winter indoor air temperature "most time feeling" has 2 (2.6%) missing values Missing
Do you feel comfortable under the current temperature ? has 2 (2.6%) missing values Missing
How you describe the current temperature in this room? has 2 (2.6%) missing values Missing
Does the distraction from noise in this part of building have a negative effect on your work performance "most time feeling"? has 2 (2.6%) missing values Missing
Is there significant distraction from noise outside (in this moment) ? has 2 (2.6%) missing values Missing
Is there significant distraction from background noise (machine and undefined noise sources)? has 2 (2.6%) missing values Missing
How would you describe the noise in building generally "most time feeling"? has 2 (2.6%) missing values Missing
How would describe noise at this moment? has 34 (43.6%) missing values Missing
Does the quality of air in this part of building have a negative effect on your work performance "most time feeling"? has 34 (43.6%) missing values Missing
Do you have control over air condition system ? has 34 (43.6%) missing values Missing
How would you describe the ventilation and air quality of building "most time feeling"? has 34 (43.6%) missing values Missing
Do you smell odor or unusual smell in your work-space "most time feeling"? has 34 (43.6%) missing values Missing
Do you feel sleepy or headache when you get to your work-space "most time feeling"? has 34 (43.6%) missing values Missing
Right now, do you smell unusual smell? has 34 (43.6%) missing values Missing
Does the quality of light (color and light level) in this part of building have a negative effect on your work performance ? has 34 (43.6%) missing values Missing
Is there availability of natural light? has 34 (43.6%) missing values Missing
Are there blinds or shutters blocking the natural light ? has 34 (43.6%) missing values Missing
Do you have control over artificial lightning ? has 34 (43.6%) missing values Missing
Is there any luminare is OFF at this moment? has 34 (43.6%) missing values Missing
Unnamed: 61 has 55 (70.5%) missing values Missing
Unnamed: 62 has 55 (70.5%) missing values Missing
Unnamed: 63 has 55 (70.5%) missing values Missing
Unnamed: 64 has 55 (70.5%) missing values Missing
Unnamed: 65 has 55 (70.5%) missing values Missing
Unnamed: 66 has 55 (70.5%) missing values Missing
Time is uniformly distributed Uniform
Decimal is uniformly distributed Uniform
Illumination level (Lux) is uniformly distributed Uniform
Color Tempreture is uniformly distributed Uniform
Average Noise level is uniformly distributed Uniform
O2 Concentration (%Vol) is uniformly distributed Uniform
CO2 at any moment (PPM) is uniformly distributed Uniform
LPG concen (ppm) is uniformly distributed Uniform
Methan Concen (ppm) is uniformly distributed Uniform
CO concen (ppm) is uniformly distributed Uniform
Hydrogyn Concen (ppm) is uniformly distributed Uniform
Netric tVOC level (ppm) is uniformly distributed Uniform
VOC Formerdahied Level (ppm) is uniformly distributed Uniform
Room Temp ( C ) is uniformly distributed Uniform
Room reative humadity % is uniformly distributed Uniform
Radiant Temp 1 (C).1 is uniformly distributed Uniform
Timestamp is uniformly distributed Uniform

Reproduction

Analysis started2022-08-24 12:05:53.594972
Analysis finished2022-08-24 12:06:51.651565
Duration58.06 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

Location
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct19
Distinct (%)25.0%
Missing2
Missing (%)2.6%
Memory size752.0 B
STU211
31 
STU203
Corridor
STU301
STU202
Other values (14)
25 

Length

Max length9
Median length6
Mean length6.276315789
Min length5

Characters and Unicode

Total characters477
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)7.9%

Sample

1st rowSTU302
2nd rowSTU302
3rd rowSTU 302
4th rowSTU207
5th rowSTU207

Common Values

ValueCountFrequency (%)
STU21131
39.7%
STU2036
 
7.7%
Corridor 5
 
6.4%
STU3015
 
6.4%
STU2024
 
5.1%
Lobby3
 
3.8%
STU304 3
 
3.8%
CL302 3
 
3.8%
Location 2
 
2.6%
STU302 2
 
2.6%
Other values (9)12
 
15.4%

Length

2022-08-24T15:06:51.755248image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
stu21131
40.3%
stu2036
 
7.8%
corridor5
 
6.5%
stu3015
 
6.5%
stu2024
 
5.2%
lobby3
 
3.9%
stu3043
 
3.9%
cl3023
 
3.9%
ad3162
 
2.6%
stu2072
 
2.6%
Other values (10)13
16.9%

Most occurring characters

ValueCountFrequency (%)
173
15.3%
256
11.7%
S55
11.5%
U55
11.5%
T55
11.5%
031
6.5%
327
 
5.7%
19
 
4.0%
o17
 
3.6%
r15
 
3.1%
Other values (18)74
15.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter201
42.1%
Decimal Number196
41.1%
Lowercase Letter61
 
12.8%
Space Separator19
 
4.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S55
27.4%
U55
27.4%
T55
27.4%
L14
 
7.0%
C11
 
5.5%
A4
 
2.0%
B2
 
1.0%
D2
 
1.0%
E2
 
1.0%
V1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
o17
27.9%
r15
24.6%
i7
11.5%
b6
 
9.8%
d5
 
8.2%
y3
 
4.9%
c2
 
3.3%
a2
 
3.3%
t2
 
3.3%
n2
 
3.3%
Decimal Number
ValueCountFrequency (%)
173
37.2%
256
28.6%
031
15.8%
327
 
13.8%
44
 
2.0%
63
 
1.5%
72
 
1.0%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin262
54.9%
Common215
45.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
S55
21.0%
U55
21.0%
T55
21.0%
o17
 
6.5%
r15
 
5.7%
L14
 
5.3%
C11
 
4.2%
i7
 
2.7%
b6
 
2.3%
d5
 
1.9%
Other values (10)22
 
8.4%
Common
ValueCountFrequency (%)
173
34.0%
256
26.0%
031
14.4%
327
 
12.6%
19
 
8.8%
44
 
1.9%
63
 
1.4%
72
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII477
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
173
15.3%
256
11.7%
S55
11.5%
U55
11.5%
T55
11.5%
031
6.5%
327
 
5.7%
19
 
4.0%
o17
 
3.6%
r15
 
3.1%
Other values (18)74
15.5%

Time
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct75
Distinct (%)98.7%
Missing2
Missing (%)2.6%
Memory size752.0 B
Time
 
2
9:34:10 AM
 
1
10:00:07 AM
 
1
9:54:45 AM
 
1
9:51:10 AM
 
1
Other values (70)
70 

Length

Max length11
Median length10
Mean length10.27631579
Min length4

Characters and Unicode

Total characters781
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)97.4%

Sample

1st row2:26:26 PM
2nd row2:29:07 PM
3rd row2:31:48 PM
4th row2:46:07 PM
5th row2:53:17 PM

Common Values

ValueCountFrequency (%)
Time2
 
2.6%
9:34:10 AM1
 
1.3%
10:00:07 AM1
 
1.3%
9:54:45 AM1
 
1.3%
9:51:10 AM1
 
1.3%
9:46:42 AM1
 
1.3%
9:43:07 AM1
 
1.3%
9:38:39 AM1
 
1.3%
2:26:26 PM1
 
1.3%
10:12:39 AM1
 
1.3%
Other values (65)65
83.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:51.897786image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
am37
25.0%
pm35
23.6%
time2
 
1.4%
2:37:101
 
0.7%
3:13:521
 
0.7%
2:46:071
 
0.7%
2:53:171
 
0.7%
3:06:431
 
0.7%
0.6315277781
 
0.7%
3:10:171
 
0.7%
Other values (67)67
45.3%

Most occurring characters

ValueCountFrequency (%)
:144
18.4%
1100
12.8%
72
9.2%
M72
9.2%
258
7.4%
048
 
6.1%
447
 
6.0%
345
 
5.8%
A37
 
4.7%
P35
 
4.5%
Other values (10)123
15.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number411
52.6%
Other Punctuation146
 
18.7%
Uppercase Letter146
 
18.7%
Space Separator72
 
9.2%
Lowercase Letter6
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1100
24.3%
258
14.1%
048
11.7%
447
11.4%
345
10.9%
532
 
7.8%
727
 
6.6%
923
 
5.6%
618
 
4.4%
813
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
M72
49.3%
A37
25.3%
P35
24.0%
T2
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
i2
33.3%
e2
33.3%
m2
33.3%
Other Punctuation
ValueCountFrequency (%)
:144
98.6%
.2
 
1.4%
Space Separator
ValueCountFrequency (%)
72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common629
80.5%
Latin152
 
19.5%

Most frequent character per script

Common
ValueCountFrequency (%)
:144
22.9%
1100
15.9%
72
11.4%
258
9.2%
048
 
7.6%
447
 
7.5%
345
 
7.2%
532
 
5.1%
727
 
4.3%
923
 
3.7%
Other values (3)33
 
5.2%
Latin
ValueCountFrequency (%)
M72
47.4%
A37
24.3%
P35
23.0%
T2
 
1.3%
i2
 
1.3%
e2
 
1.3%
m2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII781
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
:144
18.4%
1100
12.8%
72
9.2%
M72
9.2%
258
7.4%
048
 
6.1%
447
 
6.0%
345
 
5.8%
A37
 
4.7%
P35
 
4.5%
Other values (10)123
15.7%

Decimal
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct72
Distinct (%)98.6%
Missing5
Missing (%)6.4%
Memory size752.0 B
Decimal
 
2
10.2108
 
1
10.0019
 
1
9.9125
 
1
9.8528
 
1
Other values (67)
67 

Length

Max length7
Median length7
Mean length6.767123288
Min length4

Characters and Unicode

Total characters494
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)97.3%

Sample

1st row14.7686
2nd row14.8881
3rd row15.1119
4th row15.1567
5th row15.1714

Common Values

ValueCountFrequency (%)
Decimal2
 
2.6%
10.21081
 
1.3%
10.00191
 
1.3%
9.91251
 
1.3%
9.85281
 
1.3%
9.77831
 
1.3%
9.71861
 
1.3%
9.64421
 
1.3%
9.56941
 
1.3%
9.4951
 
1.3%
Other values (62)62
79.5%
(Missing)5
 
6.4%

Length

2022-08-24T15:06:52.034535image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
decimal2
 
2.7%
10.21081
 
1.4%
14.88811
 
1.4%
15.11191
 
1.4%
15.15671
 
1.4%
15.17141
 
1.4%
15.20141
 
1.4%
15.23111
 
1.4%
12.11361
 
1.4%
11.35281
 
1.4%
Other values (62)62
84.9%

Most occurring characters

ValueCountFrequency (%)
1109
22.1%
.71
14.4%
446
9.3%
336
 
7.3%
635
 
7.1%
534
 
6.9%
734
 
6.9%
232
 
6.5%
932
 
6.5%
027
 
5.5%
Other values (8)38
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number409
82.8%
Other Punctuation71
 
14.4%
Lowercase Letter12
 
2.4%
Uppercase Letter2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1109
26.7%
446
11.2%
336
 
8.8%
635
 
8.6%
534
 
8.3%
734
 
8.3%
232
 
7.8%
932
 
7.8%
027
 
6.6%
824
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
i2
16.7%
m2
16.7%
a2
16.7%
l2
16.7%
c2
16.7%
e2
16.7%
Other Punctuation
ValueCountFrequency (%)
.71
100.0%
Uppercase Letter
ValueCountFrequency (%)
D2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common480
97.2%
Latin14
 
2.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1109
22.7%
.71
14.8%
446
9.6%
336
 
7.5%
635
 
7.3%
534
 
7.1%
734
 
7.1%
232
 
6.7%
932
 
6.7%
027
 
5.6%
Latin
ValueCountFrequency (%)
i2
14.3%
m2
14.3%
a2
14.3%
l2
14.3%
c2
14.3%
e2
14.3%
D2
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII494
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1109
22.1%
.71
14.4%
446
9.3%
336
 
7.3%
635
 
7.1%
534
 
6.9%
734
 
6.9%
232
 
6.5%
932
 
6.5%
027
 
5.5%
Other values (8)38
 
7.7%

Illumination level (Lux)
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct75
Distinct (%)98.7%
Missing2
Missing (%)2.6%
Memory size752.0 B
Illumination level (Lux)
 
2
151.495
 
1
54.5
 
1
47.9588
 
1
63.576
 
1
Other values (70)
70 

Length

Max length24
Median length8
Mean length7.328947368
Min length4

Characters and Unicode

Total characters557
Distinct characters27
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)97.4%

Sample

1st row439.1667
2nd row436.96
3rd row443.7183
4th row240.308
5th row190.67

Common Values

ValueCountFrequency (%)
Illumination level (Lux)2
 
2.6%
151.4951
 
1.3%
54.51
 
1.3%
47.95881
 
1.3%
63.5761
 
1.3%
58.57751
 
1.3%
427.9211
 
1.3%
358.1221
 
1.3%
439.16671
 
1.3%
85.71111
 
1.3%
Other values (65)65
83.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:52.172079image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
illumination2
 
2.5%
lux2
 
2.5%
level2
 
2.5%
437.73331
 
1.2%
438.521
 
1.2%
190.671
 
1.2%
376.49671
 
1.2%
154.29251
 
1.2%
563.3651
 
1.2%
463.00751
 
1.2%
Other values (67)67
83.8%

Most occurring characters

ValueCountFrequency (%)
.74
13.3%
563
11.3%
158
10.4%
354
9.7%
448
8.6%
744
7.9%
844
7.9%
640
7.2%
240
7.2%
925
 
4.5%
Other values (17)67
12.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number435
78.1%
Other Punctuation74
 
13.3%
Lowercase Letter36
 
6.5%
Space Separator4
 
0.7%
Uppercase Letter4
 
0.7%
Close Punctuation2
 
0.4%
Open Punctuation2
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l8
22.2%
n4
11.1%
e4
11.1%
i4
11.1%
u4
11.1%
x2
 
5.6%
v2
 
5.6%
o2
 
5.6%
t2
 
5.6%
a2
 
5.6%
Decimal Number
ValueCountFrequency (%)
563
14.5%
158
13.3%
354
12.4%
448
11.0%
744
10.1%
844
10.1%
640
9.2%
240
9.2%
925
 
5.7%
019
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
I2
50.0%
L2
50.0%
Other Punctuation
ValueCountFrequency (%)
.74
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common517
92.8%
Latin40
 
7.2%

Most frequent character per script

Common
ValueCountFrequency (%)
.74
14.3%
563
12.2%
158
11.2%
354
10.4%
448
9.3%
744
8.5%
844
8.5%
640
7.7%
240
7.7%
925
 
4.8%
Other values (4)27
 
5.2%
Latin
ValueCountFrequency (%)
l8
20.0%
n4
10.0%
e4
10.0%
i4
10.0%
u4
10.0%
I2
 
5.0%
x2
 
5.0%
v2
 
5.0%
o2
 
5.0%
t2
 
5.0%
Other values (3)6
15.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII557
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.74
13.3%
563
11.3%
158
10.4%
354
9.7%
448
8.6%
744
7.9%
844
7.9%
640
7.2%
240
7.2%
925
 
4.5%
Other values (17)67
12.0%

Color Tempreture
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct74
Distinct (%)97.4%
Missing2
Missing (%)2.6%
Memory size752.0 B
Color Tempreture
 
2
6003
 
2
7727.8
 
1
7173.6429
 
1
7159
 
1
Other values (69)
69 

Length

Max length16
Median length9
Mean length6.460526316
Min length4

Characters and Unicode

Total characters491
Distinct characters22
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)94.7%

Sample

1st row7163.3333
2nd row7256
3rd row7272.3333
4th row6369
5th row6010.1667

Common Values

ValueCountFrequency (%)
Color Tempreture2
 
2.6%
60032
 
2.6%
7727.81
 
1.3%
7173.64291
 
1.3%
71591
 
1.3%
7152.251
 
1.3%
7156.21
 
1.3%
7050.51
 
1.3%
7235.21
 
1.3%
7163.33331
 
1.3%
Other values (64)64
82.1%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:52.313162image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
color2
 
2.6%
60032
 
2.6%
tempreture2
 
2.6%
7055.66671
 
1.3%
7975.16671
 
1.3%
6010.16671
 
1.3%
68341
 
1.3%
6017.51
 
1.3%
79431
 
1.3%
7540.57141
 
1.3%
Other values (65)65
83.3%

Most occurring characters

ValueCountFrequency (%)
777
15.7%
659
12.0%
358
11.8%
.47
9.6%
545
9.2%
241
8.4%
139
7.9%
030
 
6.1%
424
 
4.9%
923
 
4.7%
Other values (12)48
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number412
83.9%
Other Punctuation47
 
9.6%
Lowercase Letter26
 
5.3%
Uppercase Letter4
 
0.8%
Space Separator2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
777
18.7%
659
14.3%
358
14.1%
545
10.9%
241
10.0%
139
9.5%
030
 
7.3%
424
 
5.8%
923
 
5.6%
816
 
3.9%
Lowercase Letter
ValueCountFrequency (%)
e6
23.1%
r6
23.1%
o4
15.4%
l2
 
7.7%
u2
 
7.7%
t2
 
7.7%
p2
 
7.7%
m2
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
T2
50.0%
C2
50.0%
Other Punctuation
ValueCountFrequency (%)
.47
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common461
93.9%
Latin30
 
6.1%

Most frequent character per script

Common
ValueCountFrequency (%)
777
16.7%
659
12.8%
358
12.6%
.47
10.2%
545
9.8%
241
8.9%
139
8.5%
030
 
6.5%
424
 
5.2%
923
 
5.0%
Other values (2)18
 
3.9%
Latin
ValueCountFrequency (%)
e6
20.0%
r6
20.0%
o4
13.3%
T2
 
6.7%
l2
 
6.7%
u2
 
6.7%
t2
 
6.7%
p2
 
6.7%
m2
 
6.7%
C2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII491
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
777
15.7%
659
12.0%
358
11.8%
.47
9.6%
545
9.2%
241
8.4%
139
7.9%
030
 
6.1%
424
 
4.9%
923
 
4.7%
Other values (12)48
9.8%

Average Noise level
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct74
Distinct (%)97.4%
Missing2
Missing (%)2.6%
Memory size752.0 B
Average Noise level
 
2
26.15
 
2
62.177
 
1
27.9107
 
1
23.0111
 
1
Other values (69)
69 

Length

Max length19
Median length7
Mean length6.881578947
Min length4

Characters and Unicode

Total characters523
Distinct characters23
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)94.7%

Sample

1st row29.2722
2nd row27.1722
3rd row28.1833
4th row26.4233
5th row29.5139

Common Values

ValueCountFrequency (%)
Average Noise level2
 
2.6%
26.152
 
2.6%
62.1771
 
1.3%
27.91071
 
1.3%
23.01111
 
1.3%
48.90421
 
1.3%
45.84331
 
1.3%
25.50421
 
1.3%
23.981
 
1.3%
29.27221
 
1.3%
Other values (64)64
82.1%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:52.446857image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
average2
 
2.5%
26.152
 
2.5%
noise2
 
2.5%
level2
 
2.5%
57.751
 
1.2%
26.42331
 
1.2%
29.51391
 
1.2%
24.91111
 
1.2%
58.65831
 
1.2%
58.56671
 
1.2%
Other values (66)66
82.5%

Most occurring characters

ValueCountFrequency (%)
.74
14.1%
270
13.4%
359
11.3%
148
9.2%
546
8.8%
744
8.4%
637
7.1%
433
6.3%
930
5.7%
824
 
4.6%
Other values (13)58
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number411
78.6%
Other Punctuation74
 
14.1%
Lowercase Letter30
 
5.7%
Space Separator4
 
0.8%
Uppercase Letter4
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
270
17.0%
359
14.4%
148
11.7%
546
11.2%
744
10.7%
637
9.0%
433
8.0%
930
7.3%
824
 
5.8%
020
 
4.9%
Lowercase Letter
ValueCountFrequency (%)
e10
33.3%
l4
 
13.3%
v4
 
13.3%
s2
 
6.7%
i2
 
6.7%
o2
 
6.7%
g2
 
6.7%
a2
 
6.7%
r2
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
N2
50.0%
A2
50.0%
Other Punctuation
ValueCountFrequency (%)
.74
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common489
93.5%
Latin34
 
6.5%

Most frequent character per script

Common
ValueCountFrequency (%)
.74
15.1%
270
14.3%
359
12.1%
148
9.8%
546
9.4%
744
9.0%
637
7.6%
433
6.7%
930
6.1%
824
 
4.9%
Other values (2)24
 
4.9%
Latin
ValueCountFrequency (%)
e10
29.4%
l4
 
11.8%
v4
 
11.8%
s2
 
5.9%
i2
 
5.9%
o2
 
5.9%
N2
 
5.9%
g2
 
5.9%
a2
 
5.9%
r2
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII523
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.74
14.1%
270
13.4%
359
11.3%
148
9.2%
546
8.8%
744
8.4%
637
7.1%
433
6.3%
930
5.7%
824
 
4.6%
Other values (13)58
11.1%

O2 Concentration (%Vol)
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct66
Distinct (%)86.8%
Missing2
Missing (%)2.6%
Memory size752.0 B
20.49
 
3
20.74
 
2
20.31
 
2
O2 Concentration (%Vol)
 
2
20.55
 
2
Other values (61)
65 

Length

Max length23
Median length7
Mean length6.368421053
Min length4

Characters and Unicode

Total characters484
Distinct characters27
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)75.0%

Sample

1st row20.4633
2nd row20.47
3rd row20.4967
4th row20.622
5th row20.58

Common Values

ValueCountFrequency (%)
20.493
 
3.8%
20.742
 
2.6%
20.312
 
2.6%
O2 Concentration (%Vol)2
 
2.6%
20.552
 
2.6%
20.4252
 
2.6%
20.332
 
2.6%
20.2562
 
2.6%
20.49672
 
2.6%
20.1921
 
1.3%
Other values (56)56
71.8%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:52.796736image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20.493
 
3.8%
20.552
 
2.5%
20.742
 
2.5%
20.49672
 
2.5%
20.2562
 
2.5%
20.4252
 
2.5%
20.332
 
2.5%
vol2
 
2.5%
concentration2
 
2.5%
o22
 
2.5%
Other values (58)59
73.8%

Most occurring characters

ValueCountFrequency (%)
2106
21.9%
079
16.3%
.74
15.3%
337
 
7.6%
533
 
6.8%
726
 
5.4%
623
 
4.8%
421
 
4.3%
116
 
3.3%
913
 
2.7%
Other values (17)56
11.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number366
75.6%
Other Punctuation76
 
15.7%
Lowercase Letter28
 
5.8%
Uppercase Letter6
 
1.2%
Space Separator4
 
0.8%
Open Punctuation2
 
0.4%
Close Punctuation2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2106
29.0%
079
21.6%
337
 
10.1%
533
 
9.0%
726
 
7.1%
623
 
6.3%
421
 
5.7%
116
 
4.4%
913
 
3.6%
812
 
3.3%
Lowercase Letter
ValueCountFrequency (%)
o6
21.4%
n6
21.4%
t4
14.3%
e2
 
7.1%
r2
 
7.1%
a2
 
7.1%
i2
 
7.1%
l2
 
7.1%
c2
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
C2
33.3%
V2
33.3%
O2
33.3%
Other Punctuation
ValueCountFrequency (%)
.74
97.4%
%2
 
2.6%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common450
93.0%
Latin34
 
7.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2106
23.6%
079
17.6%
.74
16.4%
337
 
8.2%
533
 
7.3%
726
 
5.8%
623
 
5.1%
421
 
4.7%
116
 
3.6%
913
 
2.9%
Other values (5)22
 
4.9%
Latin
ValueCountFrequency (%)
o6
17.6%
n6
17.6%
t4
11.8%
C2
 
5.9%
e2
 
5.9%
r2
 
5.9%
a2
 
5.9%
i2
 
5.9%
V2
 
5.9%
l2
 
5.9%
Other values (2)4
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII484
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2106
21.9%
079
16.3%
.74
15.3%
337
 
7.6%
533
 
6.8%
726
 
5.4%
623
 
4.8%
421
 
4.3%
116
 
3.3%
913
 
2.7%
Other values (17)56
11.6%

CO2 at any moment (PPM)
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct75
Distinct (%)98.7%
Missing2
Missing (%)2.6%
Memory size752.0 B
CO2 at any moment (PPM)
 
2
1103.6246
 
1
1045.9584
 
1
1081.953
 
1
1104.2462
 
1
Other values (70)
70 

Length

Max length23
Median length8
Mean length8.578947368
Min length1

Characters and Unicode

Total characters652
Distinct characters26
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique74 ?
Unique (%)97.4%

Sample

1st row1280.6112
2nd row1297.6959
3rd row1280.9724
4th row1090.0868
5th row1070.3733

Common Values

ValueCountFrequency (%)
CO2 at any moment (PPM)2
 
2.6%
1103.62461
 
1.3%
1045.95841
 
1.3%
1081.9531
 
1.3%
1104.24621
 
1.3%
1082.43861
 
1.3%
1074.84711
 
1.3%
1108.59111
 
1.3%
1280.61121
 
1.3%
1038.77731
 
1.3%
Other values (65)65
83.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:52.929085image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
co22
 
2.4%
any2
 
2.4%
moment2
 
2.4%
ppm2
 
2.4%
at2
 
2.4%
721.94561
 
1.2%
1090.08681
 
1.2%
1070.37331
 
1.2%
955.1841
 
1.2%
960.80371
 
1.2%
Other values (69)69
82.1%

Most occurring characters

ValueCountFrequency (%)
1117
17.9%
.73
11.2%
759
9.0%
855
8.4%
949
7.5%
248
7.4%
646
 
7.1%
445
 
6.9%
042
 
6.4%
338
 
5.8%
Other values (16)80
12.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number534
81.9%
Other Punctuation73
 
11.2%
Lowercase Letter22
 
3.4%
Uppercase Letter10
 
1.5%
Space Separator8
 
1.2%
Close Punctuation2
 
0.3%
Open Punctuation2
 
0.3%
Modifier Symbol1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1117
21.9%
759
11.0%
855
10.3%
949
9.2%
248
9.0%
646
 
8.6%
445
 
8.4%
042
 
7.9%
338
 
7.1%
535
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
m4
18.2%
n4
18.2%
t4
18.2%
a4
18.2%
e2
9.1%
o2
9.1%
y2
9.1%
Uppercase Letter
ValueCountFrequency (%)
P4
40.0%
C2
20.0%
M2
20.0%
O2
20.0%
Other Punctuation
ValueCountFrequency (%)
.73
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Modifier Symbol
ValueCountFrequency (%)
`1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common620
95.1%
Latin32
 
4.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1117
18.9%
.73
11.8%
759
9.5%
855
8.9%
949
7.9%
248
7.7%
646
 
7.4%
445
 
7.3%
042
 
6.8%
338
 
6.1%
Other values (5)48
7.7%
Latin
ValueCountFrequency (%)
m4
12.5%
P4
12.5%
n4
12.5%
t4
12.5%
a4
12.5%
C2
6.2%
M2
6.2%
O2
6.2%
e2
6.2%
o2
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII652
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1117
17.9%
.73
11.2%
759
9.0%
855
8.4%
949
7.5%
248
7.4%
646
 
7.1%
445
 
6.9%
042
 
6.4%
338
 
5.8%
Other values (16)80
12.3%

LPG concen (ppm)
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct73
Distinct (%)96.1%
Missing2
Missing (%)2.6%
Memory size752.0 B
3.6252
 
2
3.9178
 
2
LPG concen (ppm)
 
2
3.7988
 
1
3.0643
 
1
Other values (68)
68 

Length

Max length16
Median length6
Mean length6.144736842
Min length4

Characters and Unicode

Total characters467
Distinct characters23
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)92.1%

Sample

1st row3.886
2nd row3.9667
3rd row3.8465
4th row3.6904
5th row3.6421

Common Values

ValueCountFrequency (%)
3.62522
 
2.6%
3.91782
 
2.6%
LPG concen (ppm)2
 
2.6%
3.79881
 
1.3%
3.06431
 
1.3%
3.10661
 
1.3%
3.04351
 
1.3%
3.03961
 
1.3%
3.29741
 
1.3%
2.90271
 
1.3%
Other values (63)63
80.8%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:53.055022image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3.62522
 
2.5%
lpg2
 
2.5%
concen2
 
2.5%
ppm2
 
2.5%
3.91782
 
2.5%
3.15491
 
1.2%
3.69041
 
1.2%
3.64211
 
1.2%
3.3131
 
1.2%
3.35961
 
1.2%
Other values (65)65
81.2%

Most occurring characters

ValueCountFrequency (%)
.74
15.8%
370
15.0%
840
8.6%
240
8.6%
437
7.9%
933
7.1%
530
6.4%
030
6.4%
630
6.4%
727
 
5.8%
Other values (13)56
12.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number361
77.3%
Other Punctuation74
 
15.8%
Lowercase Letter18
 
3.9%
Uppercase Letter6
 
1.3%
Space Separator4
 
0.9%
Close Punctuation2
 
0.4%
Open Punctuation2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
370
19.4%
840
11.1%
240
11.1%
437
10.2%
933
9.1%
530
8.3%
030
8.3%
630
8.3%
727
 
7.5%
124
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
p4
22.2%
c4
22.2%
n4
22.2%
m2
11.1%
o2
11.1%
e2
11.1%
Uppercase Letter
ValueCountFrequency (%)
P2
33.3%
L2
33.3%
G2
33.3%
Other Punctuation
ValueCountFrequency (%)
.74
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common443
94.9%
Latin24
 
5.1%

Most frequent character per script

Common
ValueCountFrequency (%)
.74
16.7%
370
15.8%
840
9.0%
240
9.0%
437
8.4%
933
7.4%
530
6.8%
030
6.8%
630
6.8%
727
 
6.1%
Other values (4)32
7.2%
Latin
ValueCountFrequency (%)
p4
16.7%
c4
16.7%
n4
16.7%
m2
8.3%
o2
8.3%
e2
8.3%
P2
8.3%
L2
8.3%
G2
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII467
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.74
15.8%
370
15.0%
840
8.6%
240
8.6%
437
7.9%
933
7.1%
530
6.4%
030
6.4%
630
6.4%
727
 
5.8%
Other values (13)56
12.0%

Alcohole Concen (ppm)
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct29
Distinct (%)38.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
0.0043
0.0036
0.0035
0.0031
0.0042
Other values (24)
44 

Length

Max length21
Median length6
Mean length6.315789474
Min length5

Characters and Unicode

Total characters480
Distinct characters24
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)17.1%

Sample

1st row0.0043
2nd row0.0043
3rd row0.0043
4th row0.0043
5th row0.0042

Common Values

ValueCountFrequency (%)
0.00438
 
10.3%
0.00366
 
7.7%
0.00356
 
7.7%
0.00316
 
7.7%
0.00426
 
7.7%
0.0034
 
5.1%
0.00294
 
5.1%
0.00173
 
3.8%
0.00373
 
3.8%
0.00553
 
3.8%
Other values (19)27
34.6%

Length

2022-08-24T15:06:53.192435image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.00438
 
10.0%
0.00366
 
7.5%
0.00356
 
7.5%
0.00316
 
7.5%
0.00426
 
7.5%
0.0034
 
5.0%
0.00294
 
5.0%
0.00173
 
3.8%
0.00373
 
3.8%
0.00553
 
3.8%
Other values (21)31
38.8%

Most occurring characters

ValueCountFrequency (%)
0219
45.6%
.74
 
15.4%
341
 
8.5%
429
 
6.0%
516
 
3.3%
216
 
3.3%
113
 
2.7%
69
 
1.9%
79
 
1.9%
87
 
1.5%
Other values (14)47
 
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number364
75.8%
Other Punctuation74
 
15.4%
Lowercase Letter30
 
6.2%
Space Separator4
 
0.8%
Uppercase Letter4
 
0.8%
Open Punctuation2
 
0.4%
Close Punctuation2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0219
60.2%
341
 
11.3%
429
 
8.0%
516
 
4.4%
216
 
4.4%
113
 
3.6%
69
 
2.5%
79
 
2.5%
87
 
1.9%
95
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
o6
20.0%
e4
13.3%
p4
13.3%
n4
13.3%
l4
13.3%
c4
13.3%
h2
 
6.7%
m2
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
C2
50.0%
A2
50.0%
Other Punctuation
ValueCountFrequency (%)
.74
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common446
92.9%
Latin34
 
7.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0219
49.1%
.74
 
16.6%
341
 
9.2%
429
 
6.5%
516
 
3.6%
216
 
3.6%
113
 
2.9%
69
 
2.0%
79
 
2.0%
87
 
1.6%
Other values (4)13
 
2.9%
Latin
ValueCountFrequency (%)
o6
17.6%
e4
11.8%
p4
11.8%
n4
11.8%
l4
11.8%
c4
11.8%
h2
 
5.9%
C2
 
5.9%
A2
 
5.9%
m2
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII480
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0219
45.6%
.74
 
15.4%
341
 
8.5%
429
 
6.0%
516
 
3.3%
216
 
3.3%
113
 
2.7%
69
 
1.9%
79
 
1.9%
87
 
1.5%
Other values (14)47
 
9.8%

Methan Concen (ppm)
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct70
Distinct (%)92.1%
Missing2
Missing (%)2.6%
Memory size752.0 B
0.282
 
2
0.3118
 
2
Methan Concen (ppm)
 
2
0.3167
 
2
0.271
 
2
Other values (65)
66 

Length

Max length19
Median length6
Mean length6.171052632
Min length5

Characters and Unicode

Total characters469
Distinct characters25
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)84.2%

Sample

1st row0.2984
2nd row0.2883
3rd row0.2934
4th row0.3027
5th row0.3011

Common Values

ValueCountFrequency (%)
0.2822
 
2.6%
0.31182
 
2.6%
Methan Concen (ppm)2
 
2.6%
0.31672
 
2.6%
0.2712
 
2.6%
0.29332
 
2.6%
0.31781
 
1.3%
0.31841
 
1.3%
0.31121
 
1.3%
0.32471
 
1.3%
Other values (60)60
76.9%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:53.329604image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.2822
 
2.5%
methan2
 
2.5%
concen2
 
2.5%
ppm2
 
2.5%
0.31672
 
2.5%
0.2712
 
2.5%
0.29332
 
2.5%
0.31182
 
2.5%
0.27471
 
1.2%
0.3461
 
1.2%
Other values (62)62
77.5%

Most occurring characters

ValueCountFrequency (%)
082
17.5%
.74
15.8%
360
12.8%
247
10.0%
132
 
6.8%
729
 
6.2%
925
 
5.3%
823
 
4.9%
621
 
4.5%
420
 
4.3%
Other values (15)56
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number357
76.1%
Other Punctuation74
 
15.8%
Lowercase Letter26
 
5.5%
Space Separator4
 
0.9%
Uppercase Letter4
 
0.9%
Open Punctuation2
 
0.4%
Close Punctuation2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
082
23.0%
360
16.8%
247
13.2%
132
 
9.0%
729
 
8.1%
925
 
7.0%
823
 
6.4%
621
 
5.9%
420
 
5.6%
518
 
5.0%
Lowercase Letter
ValueCountFrequency (%)
n6
23.1%
p4
15.4%
e4
15.4%
a2
 
7.7%
o2
 
7.7%
c2
 
7.7%
m2
 
7.7%
h2
 
7.7%
t2
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
C2
50.0%
M2
50.0%
Other Punctuation
ValueCountFrequency (%)
.74
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common439
93.6%
Latin30
 
6.4%

Most frequent character per script

Common
ValueCountFrequency (%)
082
18.7%
.74
16.9%
360
13.7%
247
10.7%
132
 
7.3%
729
 
6.6%
925
 
5.7%
823
 
5.2%
621
 
4.8%
420
 
4.6%
Other values (4)26
 
5.9%
Latin
ValueCountFrequency (%)
n6
20.0%
p4
13.3%
e4
13.3%
a2
 
6.7%
C2
 
6.7%
o2
 
6.7%
c2
 
6.7%
m2
 
6.7%
h2
 
6.7%
t2
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII469
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
082
17.5%
.74
15.8%
360
12.8%
247
10.0%
132
 
6.8%
729
 
6.2%
925
 
5.3%
823
 
4.9%
621
 
4.5%
420
 
4.3%
Other values (15)56
11.9%

CO concen (ppm)
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct71
Distinct (%)93.4%
Missing2
Missing (%)2.6%
Memory size752.0 B
6.328
 
3
6.2845
 
2
CO concen (ppm)
 
2
6.8157
 
2
7.4632
 
1
Other values (66)
66 

Length

Max length15
Median length6
Mean length6.118421053
Min length4

Characters and Unicode

Total characters465
Distinct characters22
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)88.2%

Sample

1st row5.7167
2nd row5.8004
3rd row5.8006
4th row6.907
5th row6.7815

Common Values

ValueCountFrequency (%)
6.3283
 
3.8%
6.28452
 
2.6%
CO concen (ppm)2
 
2.6%
6.81572
 
2.6%
7.46321
 
1.3%
7.46341
 
1.3%
6.50351
 
1.3%
6.22671
 
1.3%
6.54891
 
1.3%
6.46421
 
1.3%
Other values (61)61
78.2%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:53.462699image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
6.3283
 
3.8%
co2
 
2.5%
concen2
 
2.5%
ppm2
 
2.5%
6.81572
 
2.5%
6.28452
 
2.5%
6.59261
 
1.2%
6.9071
 
1.2%
6.78151
 
1.2%
6.95321
 
1.2%
Other values (63)63
78.8%

Most occurring characters

ValueCountFrequency (%)
.74
15.9%
667
14.4%
749
10.5%
546
9.9%
238
8.2%
433
7.1%
927
 
5.8%
827
 
5.8%
327
 
5.8%
125
 
5.4%
Other values (12)52
11.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number361
77.6%
Other Punctuation74
 
15.9%
Lowercase Letter18
 
3.9%
Space Separator4
 
0.9%
Uppercase Letter4
 
0.9%
Open Punctuation2
 
0.4%
Close Punctuation2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
667
18.6%
749
13.6%
546
12.7%
238
10.5%
433
9.1%
927
7.5%
827
7.5%
327
7.5%
125
 
6.9%
022
 
6.1%
Lowercase Letter
ValueCountFrequency (%)
c4
22.2%
n4
22.2%
p4
22.2%
e2
11.1%
m2
11.1%
o2
11.1%
Uppercase Letter
ValueCountFrequency (%)
C2
50.0%
O2
50.0%
Other Punctuation
ValueCountFrequency (%)
.74
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common443
95.3%
Latin22
 
4.7%

Most frequent character per script

Common
ValueCountFrequency (%)
.74
16.7%
667
15.1%
749
11.1%
546
10.4%
238
8.6%
433
7.4%
927
 
6.1%
827
 
6.1%
327
 
6.1%
125
 
5.6%
Other values (4)30
6.8%
Latin
ValueCountFrequency (%)
c4
18.2%
n4
18.2%
p4
18.2%
C2
9.1%
O2
9.1%
e2
9.1%
m2
9.1%
o2
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII465
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.74
15.9%
667
14.4%
749
10.5%
546
9.9%
238
8.2%
433
7.1%
927
 
5.8%
827
 
5.8%
327
 
5.8%
125
 
5.4%
Other values (12)52
11.2%

Hydrogyn Concen (ppm)
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct72
Distinct (%)94.7%
Missing2
Missing (%)2.6%
Memory size752.0 B
40.7051
 
2
40.1119
 
2
Hydrogyn Concen (ppm)
 
2
40.1967
 
2
45.48
 
1
Other values (67)
67 

Length

Max length21
Median length7
Mean length7.25
Min length5

Characters and Unicode

Total characters551
Distinct characters26
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)89.5%

Sample

1st row42.5653
2nd row43.0154
3rd row42.4246
4th row40.8067
5th row40.9872

Common Values

ValueCountFrequency (%)
40.70512
 
2.6%
40.11192
 
2.6%
Hydrogyn Concen (ppm)2
 
2.6%
40.19672
 
2.6%
45.481
 
1.3%
45.43141
 
1.3%
45.18821
 
1.3%
45.26131
 
1.3%
41.12841
 
1.3%
40.87451
 
1.3%
Other values (62)62
79.5%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:53.597949image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
40.70512
 
2.5%
hydrogyn2
 
2.5%
concen2
 
2.5%
ppm2
 
2.5%
40.19672
 
2.5%
40.11192
 
2.5%
40.02711
 
1.2%
42.41171
 
1.2%
42.4971
 
1.2%
42.83861
 
1.2%
Other values (64)64
80.0%

Most occurring characters

ValueCountFrequency (%)
498
17.8%
.74
13.4%
158
10.5%
551
9.3%
241
7.4%
637
 
6.7%
034
 
6.2%
333
 
6.0%
832
 
5.8%
731
 
5.6%
Other values (16)62
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number435
78.9%
Other Punctuation74
 
13.4%
Lowercase Letter30
 
5.4%
Space Separator4
 
0.7%
Uppercase Letter4
 
0.7%
Open Punctuation2
 
0.4%
Close Punctuation2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
498
22.5%
158
13.3%
551
11.7%
241
9.4%
637
 
8.5%
034
 
7.8%
333
 
7.6%
832
 
7.4%
731
 
7.1%
920
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
n6
20.0%
o4
13.3%
p4
13.3%
y4
13.3%
g2
 
6.7%
r2
 
6.7%
c2
 
6.7%
e2
 
6.7%
m2
 
6.7%
d2
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
H2
50.0%
C2
50.0%
Other Punctuation
ValueCountFrequency (%)
.74
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common517
93.8%
Latin34
 
6.2%

Most frequent character per script

Common
ValueCountFrequency (%)
498
19.0%
.74
14.3%
158
11.2%
551
9.9%
241
7.9%
637
 
7.2%
034
 
6.6%
333
 
6.4%
832
 
6.2%
731
 
6.0%
Other values (4)28
 
5.4%
Latin
ValueCountFrequency (%)
n6
17.6%
o4
11.8%
p4
11.8%
y4
11.8%
g2
 
5.9%
r2
 
5.9%
c2
 
5.9%
e2
 
5.9%
m2
 
5.9%
d2
 
5.9%
Other values (2)4
11.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII551
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
498
17.8%
.74
13.4%
158
10.5%
551
9.3%
241
7.4%
637
 
6.7%
034
 
6.2%
333
 
6.0%
832
 
5.8%
731
 
5.6%
Other values (16)62
11.3%

Netric tVOC level (ppm)
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct69
Distinct (%)90.8%
Missing2
Missing (%)2.6%
Memory size752.0 B
0.4071
 
4
0.4219
 
2
0.4371
 
2
Netric tVOC level (ppm)
 
2
0.3391
 
2
Other values (64)
64 

Length

Max length23
Median length6
Mean length6.381578947
Min length5

Characters and Unicode

Total characters485
Distinct characters27
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)84.2%

Sample

1st row0.3324
2nd row0.3487
3rd row0.2661
4th row0.4134
5th row0.415

Common Values

ValueCountFrequency (%)
0.40714
 
5.1%
0.42192
 
2.6%
0.43712
 
2.6%
Netric tVOC level (ppm)2
 
2.6%
0.33912
 
2.6%
0.55551
 
1.3%
0.54661
 
1.3%
0.64361
 
1.3%
0.59661
 
1.3%
0.58731
 
1.3%
Other values (59)59
75.6%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:53.740717image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.40714
 
4.9%
0.43712
 
2.4%
netric2
 
2.4%
tvoc2
 
2.4%
level2
 
2.4%
ppm2
 
2.4%
0.33912
 
2.4%
0.42192
 
2.4%
0.38811
 
1.2%
0.26921
 
1.2%
Other values (62)62
75.6%

Most occurring characters

ValueCountFrequency (%)
088
18.1%
.74
15.3%
641
8.5%
237
7.6%
335
 
7.2%
730
 
6.2%
429
 
6.0%
129
 
6.0%
927
 
5.6%
527
 
5.6%
Other values (17)68
14.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number365
75.3%
Other Punctuation74
 
15.3%
Lowercase Letter28
 
5.8%
Uppercase Letter8
 
1.6%
Space Separator6
 
1.2%
Open Punctuation2
 
0.4%
Close Punctuation2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
088
24.1%
641
11.2%
237
10.1%
335
 
9.6%
730
 
8.2%
429
 
7.9%
129
 
7.9%
927
 
7.4%
527
 
7.4%
822
 
6.0%
Lowercase Letter
ValueCountFrequency (%)
e6
21.4%
t4
14.3%
l4
14.3%
p4
14.3%
r2
 
7.1%
i2
 
7.1%
v2
 
7.1%
m2
 
7.1%
c2
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
V2
25.0%
O2
25.0%
C2
25.0%
N2
25.0%
Other Punctuation
ValueCountFrequency (%)
.74
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common449
92.6%
Latin36
 
7.4%

Most frequent character per script

Common
ValueCountFrequency (%)
088
19.6%
.74
16.5%
641
9.1%
237
8.2%
335
 
7.8%
730
 
6.7%
429
 
6.5%
129
 
6.5%
927
 
6.0%
527
 
6.0%
Other values (4)32
 
7.1%
Latin
ValueCountFrequency (%)
e6
16.7%
t4
11.1%
l4
11.1%
p4
11.1%
r2
 
5.6%
i2
 
5.6%
V2
 
5.6%
O2
 
5.6%
C2
 
5.6%
v2
 
5.6%
Other values (3)6
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII485
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
088
18.1%
.74
15.3%
641
8.5%
237
7.6%
335
 
7.2%
730
 
6.2%
429
 
6.0%
129
 
6.0%
927
 
5.6%
527
 
5.6%
Other values (17)68
14.0%

VOC Formerdahied Level (ppm)
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct69
Distinct (%)90.8%
Missing2
Missing (%)2.6%
Memory size752.0 B
0.329
 
3
0.309
 
2
0.2897
 
2
0.2536
 
2
VOC Formerdahied Level (ppm)
 
2
Other values (64)
65 

Length

Max length28
Median length6
Mean length6.434210526
Min length5

Characters and Unicode

Total characters489
Distinct characters30
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)82.9%

Sample

1st row0.4855
2nd row0.5037
3rd row0.4777
4th row0.2679
5th row0.2599

Common Values

ValueCountFrequency (%)
0.3293
 
3.8%
0.3092
 
2.6%
0.28972
 
2.6%
0.25362
 
2.6%
VOC Formerdahied Level (ppm)2
 
2.6%
0.54862
 
2.6%
0.53481
 
1.3%
0.58811
 
1.3%
0.56481
 
1.3%
0.51381
 
1.3%
Other values (59)59
75.6%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:53.875634image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0.3293
 
3.7%
formerdahied2
 
2.4%
0.54862
 
2.4%
ppm2
 
2.4%
level2
 
2.4%
0.3092
 
2.4%
voc2
 
2.4%
0.28972
 
2.4%
0.25362
 
2.4%
0.16361
 
1.2%
Other values (62)62
75.6%

Most occurring characters

ValueCountFrequency (%)
085
17.4%
.74
15.1%
540
8.2%
237
7.6%
636
7.4%
436
7.4%
329
 
5.9%
825
 
5.1%
725
 
5.1%
924
 
4.9%
Other values (20)78
16.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number359
73.4%
Other Punctuation74
 
15.1%
Lowercase Letter36
 
7.4%
Uppercase Letter10
 
2.0%
Space Separator6
 
1.2%
Close Punctuation2
 
0.4%
Open Punctuation2
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e8
22.2%
r4
11.1%
p4
11.1%
m4
11.1%
d4
11.1%
v2
 
5.6%
l2
 
5.6%
i2
 
5.6%
a2
 
5.6%
o2
 
5.6%
Decimal Number
ValueCountFrequency (%)
085
23.7%
540
11.1%
237
10.3%
636
10.0%
436
10.0%
329
 
8.1%
825
 
7.0%
725
 
7.0%
924
 
6.7%
122
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
V2
20.0%
C2
20.0%
L2
20.0%
O2
20.0%
F2
20.0%
Other Punctuation
ValueCountFrequency (%)
.74
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common443
90.6%
Latin46
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e8
17.4%
r4
 
8.7%
p4
 
8.7%
m4
 
8.7%
d4
 
8.7%
v2
 
4.3%
V2
 
4.3%
l2
 
4.3%
C2
 
4.3%
L2
 
4.3%
Other values (6)12
26.1%
Common
ValueCountFrequency (%)
085
19.2%
.74
16.7%
540
9.0%
237
8.4%
636
8.1%
436
8.1%
329
 
6.5%
825
 
5.6%
725
 
5.6%
924
 
5.4%
Other values (4)32
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
085
17.4%
.74
15.1%
540
8.2%
237
7.6%
636
7.4%
436
7.4%
329
 
5.9%
825
 
5.1%
725
 
5.1%
924
 
4.9%
Other values (20)78
16.0%

Different VOC (CO) Level (ppm)
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct63
Distinct (%)82.9%
Missing2
Missing (%)2.6%
Memory size752.0 B
3.4783
2.9605
 
4
4.0099
 
2
3.4852
 
2
Different VOC (CO) Level (ppm)
 
2
Other values (58)
58 

Length

Max length30
Median length6
Mean length6.486842105
Min length4

Characters and Unicode

Total characters493
Distinct characters29
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)76.3%

Sample

1st row3.1331
2nd row3.8327
3rd row2.9656
4th row3.6909
5th row3.8348

Common Values

ValueCountFrequency (%)
3.47838
 
10.3%
2.96054
 
5.1%
4.00992
 
2.6%
3.48522
 
2.6%
Different VOC (CO) Level (ppm)2
 
2.6%
4.44731
 
1.3%
4.18071
 
1.3%
4.52471
 
1.3%
5.95731
 
1.3%
3.84751
 
1.3%
Other values (53)53
67.9%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:54.003240image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3.47838
 
9.5%
2.96054
 
4.8%
4.00992
 
2.4%
different2
 
2.4%
voc2
 
2.4%
co2
 
2.4%
level2
 
2.4%
ppm2
 
2.4%
3.48522
 
2.4%
5.68011
 
1.2%
Other values (57)57
67.9%

Most occurring characters

ValueCountFrequency (%)
.74
15.0%
455
11.2%
746
9.3%
345
9.1%
235
7.1%
535
7.1%
633
 
6.7%
130
 
6.1%
830
 
6.1%
027
 
5.5%
Other values (19)83
16.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number359
72.8%
Other Punctuation74
 
15.0%
Lowercase Letter30
 
6.1%
Uppercase Letter14
 
2.8%
Space Separator8
 
1.6%
Open Punctuation4
 
0.8%
Close Punctuation4
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
455
15.3%
746
12.8%
345
12.5%
235
9.7%
535
9.7%
633
9.2%
130
8.4%
830
8.4%
027
7.5%
923
6.4%
Lowercase Letter
ValueCountFrequency (%)
e8
26.7%
p4
13.3%
f4
13.3%
m2
 
6.7%
l2
 
6.7%
v2
 
6.7%
t2
 
6.7%
n2
 
6.7%
i2
 
6.7%
r2
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
O4
28.6%
C4
28.6%
L2
14.3%
V2
14.3%
D2
14.3%
Other Punctuation
ValueCountFrequency (%)
.74
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
(4
100.0%
Close Punctuation
ValueCountFrequency (%)
)4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common449
91.1%
Latin44
 
8.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e8
18.2%
p4
 
9.1%
f4
 
9.1%
O4
 
9.1%
C4
 
9.1%
L2
 
4.5%
m2
 
4.5%
l2
 
4.5%
v2
 
4.5%
V2
 
4.5%
Other values (5)10
22.7%
Common
ValueCountFrequency (%)
.74
16.5%
455
12.2%
746
10.2%
345
10.0%
235
7.8%
535
7.8%
633
7.3%
130
6.7%
830
6.7%
027
 
6.0%
Other values (4)39
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII493
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
.74
15.0%
455
11.2%
746
9.3%
345
9.1%
235
7.1%
535
7.1%
633
 
6.7%
130
 
6.1%
830
 
6.1%
027
 
5.5%
Other values (19)83
16.8%

Room Temp ( C )
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct73
Distinct (%)96.1%
Missing2
Missing (%)2.6%
Memory size752.0 B
24.4
 
2
Room Temp ( C )
 
2
22.6188
 
2
22.26
 
1
22.3786
 
1
Other values (68)
68 

Length

Max length15
Median length7
Mean length6.434210526
Min length4

Characters and Unicode

Total characters489
Distinct characters21
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)92.1%

Sample

1st row25.325
2nd row25.3583
3rd row25.2417
4th row24.305
5th row24.0292

Common Values

ValueCountFrequency (%)
24.42
 
2.6%
Room Temp ( C )2
 
2.6%
22.61882
 
2.6%
22.261
 
1.3%
22.37861
 
1.3%
22.4751
 
1.3%
22.38751
 
1.3%
22.5051
 
1.3%
22.48751
 
1.3%
25.3251
 
1.3%
Other values (63)63
80.8%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:54.136024image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4
 
4.8%
24.42
 
2.4%
temp2
 
2.4%
c2
 
2.4%
22.61882
 
2.4%
room2
 
2.4%
24.39291
 
1.2%
25.24171
 
1.2%
24.3051
 
1.2%
24.02921
 
1.2%
Other values (66)66
78.6%

Most occurring characters

ValueCountFrequency (%)
2125
25.6%
.74
15.1%
558
11.9%
341
 
8.4%
736
 
7.4%
434
 
7.0%
826
 
5.3%
125
 
5.1%
624
 
4.9%
08
 
1.6%
Other values (11)38
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number385
78.7%
Other Punctuation74
 
15.1%
Lowercase Letter12
 
2.5%
Space Separator8
 
1.6%
Uppercase Letter6
 
1.2%
Close Punctuation2
 
0.4%
Open Punctuation2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2125
32.5%
558
15.1%
341
 
10.6%
736
 
9.4%
434
 
8.8%
826
 
6.8%
125
 
6.5%
624
 
6.2%
08
 
2.1%
98
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
m4
33.3%
o4
33.3%
p2
16.7%
e2
16.7%
Uppercase Letter
ValueCountFrequency (%)
C2
33.3%
T2
33.3%
R2
33.3%
Other Punctuation
ValueCountFrequency (%)
.74
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common471
96.3%
Latin18
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2125
26.5%
.74
15.7%
558
12.3%
341
 
8.7%
736
 
7.6%
434
 
7.2%
826
 
5.5%
125
 
5.3%
624
 
5.1%
08
 
1.7%
Other values (4)20
 
4.2%
Latin
ValueCountFrequency (%)
m4
22.2%
o4
22.2%
C2
11.1%
p2
11.1%
e2
11.1%
T2
11.1%
R2
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2125
25.6%
.74
15.1%
558
11.9%
341
 
8.4%
736
 
7.4%
434
 
7.0%
826
 
5.3%
125
 
5.1%
624
 
4.9%
08
 
1.6%
Other values (11)38
 
7.8%

Room reative humadity %
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct72
Distinct (%)94.7%
Missing2
Missing (%)2.6%
Memory size752.0 B
55.7
 
2
Room reative humadity %
 
2
49.2
 
2
62.975
 
2
51.2833
 
1
Other values (67)
67 

Length

Max length23
Median length7
Mean length5.973684211
Min length2

Characters and Unicode

Total characters454
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)89.5%

Sample

1st row51.2833
2nd row51.35
3rd row51.4667
4th row57.68
5th row59.3417

Common Values

ValueCountFrequency (%)
55.72
 
2.6%
Room reative humadity %2
 
2.6%
49.22
 
2.6%
62.9752
 
2.6%
51.28331
 
1.3%
61.991
 
1.3%
62.88331
 
1.3%
63.151
 
1.3%
62.531
 
1.3%
62.431
 
1.3%
Other values (62)62
79.5%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:54.267056image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
55.72
 
2.4%
reative2
 
2.4%
humadity2
 
2.4%
2
 
2.4%
49.22
 
2.4%
62.9752
 
2.4%
room2
 
2.4%
631
 
1.2%
57.681
 
1.2%
59.34171
 
1.2%
Other values (65)65
79.3%

Most occurring characters

ValueCountFrequency (%)
572
15.9%
.70
15.4%
659
13.0%
341
9.0%
239
8.6%
136
7.9%
731
6.8%
425
 
5.5%
814
 
3.1%
913
 
2.9%
Other values (16)54
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number338
74.4%
Other Punctuation72
 
15.9%
Lowercase Letter36
 
7.9%
Space Separator6
 
1.3%
Uppercase Letter2
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i4
11.1%
t4
11.1%
a4
11.1%
e4
11.1%
m4
11.1%
o4
11.1%
v2
5.6%
u2
5.6%
d2
5.6%
y2
5.6%
Other values (2)4
11.1%
Decimal Number
ValueCountFrequency (%)
572
21.3%
659
17.5%
341
12.1%
239
11.5%
136
10.7%
731
9.2%
425
 
7.4%
814
 
4.1%
913
 
3.8%
08
 
2.4%
Other Punctuation
ValueCountFrequency (%)
.70
97.2%
%2
 
2.8%
Space Separator
ValueCountFrequency (%)
6
100.0%
Uppercase Letter
ValueCountFrequency (%)
R2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common416
91.6%
Latin38
 
8.4%

Most frequent character per script

Common
ValueCountFrequency (%)
572
17.3%
.70
16.8%
659
14.2%
341
9.9%
239
9.4%
136
8.7%
731
7.5%
425
 
6.0%
814
 
3.4%
913
 
3.1%
Other values (3)16
 
3.8%
Latin
ValueCountFrequency (%)
i4
10.5%
t4
10.5%
a4
10.5%
e4
10.5%
m4
10.5%
o4
10.5%
v2
 
5.3%
u2
 
5.3%
d2
 
5.3%
y2
 
5.3%
Other values (3)6
15.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII454
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
572
15.9%
.70
15.4%
659
13.0%
341
9.0%
239
8.6%
136
7.9%
731
6.8%
425
 
5.5%
814
 
3.1%
913
 
2.9%
Other values (16)54
11.9%

Radiant Temp 1 (C)
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct45
Distinct (%)59.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
21
23
20
 
4
24
 
3
23.5
 
3
Other values (40)
52 

Length

Max length18
Median length7
Mean length4.513157895
Min length2

Characters and Unicode

Total characters343
Distinct characters25
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)36.8%

Sample

1st row24
2nd row23
3rd row23.6667
4th row21
5th row19.3333

Common Values

ValueCountFrequency (%)
217
 
9.0%
237
 
9.0%
204
 
5.1%
243
 
3.8%
23.53
 
3.8%
Radiant Temp 1 (C)2
 
2.6%
21.62
 
2.6%
20.33332
 
2.6%
21.52
 
2.6%
182
 
2.6%
Other values (35)42
53.8%

Length

2022-08-24T15:06:54.397800image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
217
 
8.5%
237
 
8.5%
204
 
4.9%
243
 
3.7%
23.53
 
3.7%
182
 
2.4%
22.66672
 
2.4%
22.52
 
2.4%
222
 
2.4%
20.66672
 
2.4%
Other values (38)48
58.5%

Most occurring characters

ValueCountFrequency (%)
280
23.3%
.45
13.1%
338
11.1%
138
11.1%
627
 
7.9%
523
 
6.7%
715
 
4.4%
015
 
4.4%
810
 
2.9%
99
 
2.6%
Other values (15)43
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number264
77.0%
Other Punctuation45
 
13.1%
Lowercase Letter18
 
5.2%
Space Separator6
 
1.7%
Uppercase Letter6
 
1.7%
Open Punctuation2
 
0.6%
Close Punctuation2
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
280
30.3%
338
14.4%
138
14.4%
627
 
10.2%
523
 
8.7%
715
 
5.7%
015
 
5.7%
810
 
3.8%
99
 
3.4%
49
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
a4
22.2%
m2
11.1%
p2
11.1%
e2
11.1%
n2
11.1%
i2
11.1%
d2
11.1%
t2
11.1%
Uppercase Letter
ValueCountFrequency (%)
R2
33.3%
C2
33.3%
T2
33.3%
Other Punctuation
ValueCountFrequency (%)
.45
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common319
93.0%
Latin24
 
7.0%

Most frequent character per script

Common
ValueCountFrequency (%)
280
25.1%
.45
14.1%
338
11.9%
138
11.9%
627
 
8.5%
523
 
7.2%
715
 
4.7%
015
 
4.7%
810
 
3.1%
99
 
2.8%
Other values (4)19
 
6.0%
Latin
ValueCountFrequency (%)
a4
16.7%
R2
8.3%
C2
8.3%
m2
8.3%
p2
8.3%
e2
8.3%
T2
8.3%
n2
8.3%
i2
8.3%
d2
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII343
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
280
23.3%
.45
13.1%
338
11.1%
138
11.1%
627
 
7.9%
523
 
6.7%
715
 
4.4%
015
 
4.4%
810
 
2.9%
99
 
2.6%
Other values (15)43
12.5%

Radiant Temp 2 (C)
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct44
Distinct (%)57.9%
Missing2
Missing (%)2.6%
Memory size752.0 B
23
 
5
19
 
4
24
 
4
24.3333
 
4
22
 
4
Other values (39)
55 

Length

Max length18
Median length7
Mean length4.644736842
Min length2

Characters and Unicode

Total characters353
Distinct characters25
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)34.2%

Sample

1st row24.6667
2nd row24.3333
3rd row24.3333
4th row23
5th row20.3333

Common Values

ValueCountFrequency (%)
235
 
6.4%
194
 
5.1%
244
 
5.1%
24.33334
 
5.1%
224
 
5.1%
23.66673
 
3.8%
25.53
 
3.8%
213
 
3.8%
23.252
 
2.6%
202
 
2.6%
Other values (34)42
53.8%

Length

2022-08-24T15:06:54.539174image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
235
 
6.1%
244
 
4.9%
24.33334
 
4.9%
224
 
4.9%
194
 
4.9%
23.66673
 
3.7%
25.53
 
3.7%
213
 
3.7%
22
 
2.4%
24.752
 
2.4%
Other values (37)48
58.5%

Most occurring characters

ValueCountFrequency (%)
288
24.9%
.47
13.3%
344
12.5%
633
 
9.3%
126
 
7.4%
522
 
6.2%
420
 
5.7%
720
 
5.7%
88
 
2.3%
96
 
1.7%
Other values (15)39
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number272
77.1%
Other Punctuation47
 
13.3%
Lowercase Letter18
 
5.1%
Space Separator6
 
1.7%
Uppercase Letter6
 
1.7%
Open Punctuation2
 
0.6%
Close Punctuation2
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
288
32.4%
344
16.2%
633
 
12.1%
126
 
9.6%
522
 
8.1%
420
 
7.4%
720
 
7.4%
88
 
2.9%
96
 
2.2%
05
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
a4
22.2%
d2
11.1%
i2
11.1%
n2
11.1%
t2
11.1%
e2
11.1%
m2
11.1%
p2
11.1%
Uppercase Letter
ValueCountFrequency (%)
R2
33.3%
T2
33.3%
C2
33.3%
Other Punctuation
ValueCountFrequency (%)
.47
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common329
93.2%
Latin24
 
6.8%

Most frequent character per script

Common
ValueCountFrequency (%)
288
26.7%
.47
14.3%
344
13.4%
633
 
10.0%
126
 
7.9%
522
 
6.7%
420
 
6.1%
720
 
6.1%
88
 
2.4%
96
 
1.8%
Other values (4)15
 
4.6%
Latin
ValueCountFrequency (%)
a4
16.7%
d2
8.3%
i2
8.3%
n2
8.3%
t2
8.3%
R2
8.3%
T2
8.3%
e2
8.3%
m2
8.3%
p2
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII353
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
288
24.9%
.47
13.3%
344
12.5%
633
 
9.3%
126
 
7.4%
522
 
6.2%
420
 
5.7%
720
 
5.7%
88
 
2.3%
96
 
1.7%
Other values (15)39
11.0%

Radiant Temp 3 (C)
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct42
Distinct (%)55.3%
Missing2
Missing (%)2.6%
Memory size752.0 B
25
24
23
 
5
27
 
4
22
 
4
Other values (37)
50 

Length

Max length18
Median length7
Mean length4.276315789
Min length2

Characters and Unicode

Total characters325
Distinct characters25
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)36.8%

Sample

1st row24
2nd row25
3rd row27
4th row24
5th row22.6667

Common Values

ValueCountFrequency (%)
257
 
9.0%
246
 
7.7%
235
 
6.4%
274
 
5.1%
224
 
5.1%
214
 
5.1%
22.66673
 
3.8%
203
 
3.8%
23.86672
 
2.6%
23.22
 
2.6%
Other values (32)36
46.2%

Length

2022-08-24T15:06:54.680978image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
257
 
8.5%
246
 
7.3%
235
 
6.1%
274
 
4.9%
224
 
4.9%
214
 
4.9%
22.66673
 
3.7%
203
 
3.7%
temp2
 
2.4%
25.33332
 
2.4%
Other values (35)42
51.2%

Most occurring characters

ValueCountFrequency (%)
288
27.1%
.38
11.7%
337
11.4%
530
 
9.2%
625
 
7.7%
421
 
6.5%
719
 
5.8%
116
 
4.9%
810
 
3.1%
6
 
1.8%
Other values (15)35
 
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number253
77.8%
Other Punctuation38
 
11.7%
Lowercase Letter18
 
5.5%
Space Separator6
 
1.8%
Uppercase Letter6
 
1.8%
Close Punctuation2
 
0.6%
Open Punctuation2
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
288
34.8%
337
14.6%
530
 
11.9%
625
 
9.9%
421
 
8.3%
719
 
7.5%
116
 
6.3%
810
 
4.0%
05
 
2.0%
92
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
a4
22.2%
e2
11.1%
p2
11.1%
m2
11.1%
d2
11.1%
t2
11.1%
n2
11.1%
i2
11.1%
Uppercase Letter
ValueCountFrequency (%)
C2
33.3%
T2
33.3%
R2
33.3%
Other Punctuation
ValueCountFrequency (%)
.38
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common301
92.6%
Latin24
 
7.4%

Most frequent character per script

Common
ValueCountFrequency (%)
288
29.2%
.38
12.6%
337
12.3%
530
 
10.0%
625
 
8.3%
421
 
7.0%
719
 
6.3%
116
 
5.3%
810
 
3.3%
6
 
2.0%
Other values (4)11
 
3.7%
Latin
ValueCountFrequency (%)
a4
16.7%
e2
8.3%
C2
8.3%
p2
8.3%
m2
8.3%
d2
8.3%
T2
8.3%
t2
8.3%
n2
8.3%
i2
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII325
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
288
27.1%
.38
11.7%
337
11.4%
530
 
9.2%
625
 
7.7%
421
 
6.5%
719
 
5.8%
116
 
4.9%
810
 
3.1%
6
 
1.8%
Other values (15)35
 
10.8%

Radiant Temp 1 (C).1
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING
UNIFORM

Distinct63
Distinct (%)82.9%
Missing2
Missing (%)2.6%
Memory size752.0 B
21
 
3
22
 
3
19
 
2
23
 
2
Radiant Temp 1 (C)
 
2
Other values (58)
64 

Length

Max length18
Median length7
Mean length5.921052632
Min length2

Characters and Unicode

Total characters450
Distinct characters25
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)68.4%

Sample

1st row24.2222
2nd row24.1111
3rd row25
4th row22.6667
5th row20.7778

Common Values

ValueCountFrequency (%)
213
 
3.8%
223
 
3.8%
192
 
2.6%
232
 
2.6%
Radiant Temp 1 (C)2
 
2.6%
26.252
 
2.6%
22.06672
 
2.6%
202
 
2.6%
242
 
2.6%
24.11112
 
2.6%
Other values (53)54
69.2%

Length

2022-08-24T15:06:54.823965image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
213
 
3.7%
223
 
3.7%
26.252
 
2.4%
22.73332
 
2.4%
242
 
2.4%
202
 
2.4%
22.06672
 
2.4%
24.11112
 
2.4%
c2
 
2.4%
temp2
 
2.4%
Other values (56)60
73.2%

Most occurring characters

ValueCountFrequency (%)
2109
24.2%
.57
12.7%
355
12.2%
639
 
8.7%
737
 
8.2%
132
 
7.1%
422
 
4.9%
822
 
4.9%
521
 
4.7%
012
 
2.7%
Other values (15)44
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number359
79.8%
Other Punctuation57
 
12.7%
Lowercase Letter18
 
4.0%
Space Separator6
 
1.3%
Uppercase Letter6
 
1.3%
Close Punctuation2
 
0.4%
Open Punctuation2
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2109
30.4%
355
15.3%
639
 
10.9%
737
 
10.3%
132
 
8.9%
422
 
6.1%
822
 
6.1%
521
 
5.8%
012
 
3.3%
910
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
a4
22.2%
n2
11.1%
d2
11.1%
t2
11.1%
p2
11.1%
m2
11.1%
i2
11.1%
e2
11.1%
Uppercase Letter
ValueCountFrequency (%)
R2
33.3%
C2
33.3%
T2
33.3%
Other Punctuation
ValueCountFrequency (%)
.57
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common426
94.7%
Latin24
 
5.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2109
25.6%
.57
13.4%
355
12.9%
639
 
9.2%
737
 
8.7%
132
 
7.5%
422
 
5.2%
822
 
5.2%
521
 
4.9%
012
 
2.8%
Other values (4)20
 
4.7%
Latin
ValueCountFrequency (%)
a4
16.7%
n2
8.3%
R2
8.3%
d2
8.3%
C2
8.3%
t2
8.3%
p2
8.3%
m2
8.3%
i2
8.3%
T2
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII450
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2109
24.2%
.57
12.7%
355
12.2%
639
 
8.7%
737
 
8.2%
132
 
7.1%
422
 
4.9%
822
 
4.9%
521
 
4.7%
012
 
2.7%
Other values (15)44
9.8%

Wind Speed (mm/s)
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct53
Distinct (%)69.7%
Missing2
Missing (%)2.6%
Memory size752.0 B
136
134
137
 
5
135.3333
 
3
135
 
3
Other values (48)
52 

Length

Max length17
Median length8
Mean length5.421052632
Min length3

Characters and Unicode

Total characters412
Distinct characters24
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)59.2%

Sample

1st row132.6667
2nd row130.3333
3rd row133.6667
4th row136.2
5th row137.5

Common Values

ValueCountFrequency (%)
1367
 
9.0%
1346
 
7.7%
1375
 
6.4%
135.33333
 
3.8%
1353
 
3.8%
1323
 
3.8%
Wind Speed (mm/s)2
 
2.6%
1382
 
2.6%
136.42861
 
1.3%
134.81
 
1.3%
Other values (43)43
55.1%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:54.962611image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1367
 
8.8%
1346
 
7.5%
1375
 
6.2%
135.33333
 
3.8%
1353
 
3.8%
1323
 
3.8%
wind2
 
2.5%
speed2
 
2.5%
mm/s2
 
2.5%
1382
 
2.5%
Other values (45)45
56.2%

Most occurring characters

ValueCountFrequency (%)
3113
27.4%
180
19.4%
.43
 
10.4%
636
 
8.7%
527
 
6.6%
724
 
5.8%
219
 
4.6%
415
 
3.6%
811
 
2.7%
95
 
1.2%
Other values (14)39
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number335
81.3%
Other Punctuation45
 
10.9%
Lowercase Letter20
 
4.9%
Space Separator4
 
1.0%
Uppercase Letter4
 
1.0%
Open Punctuation2
 
0.5%
Close Punctuation2
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3113
33.7%
180
23.9%
636
 
10.7%
527
 
8.1%
724
 
7.2%
219
 
5.7%
415
 
4.5%
811
 
3.3%
95
 
1.5%
05
 
1.5%
Lowercase Letter
ValueCountFrequency (%)
d4
20.0%
e4
20.0%
m4
20.0%
n2
10.0%
p2
10.0%
s2
10.0%
i2
10.0%
Other Punctuation
ValueCountFrequency (%)
.43
95.6%
/2
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
S2
50.0%
W2
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common388
94.2%
Latin24
 
5.8%

Most frequent character per script

Common
ValueCountFrequency (%)
3113
29.1%
180
20.6%
.43
 
11.1%
636
 
9.3%
527
 
7.0%
724
 
6.2%
219
 
4.9%
415
 
3.9%
811
 
2.8%
95
 
1.3%
Other values (5)15
 
3.9%
Latin
ValueCountFrequency (%)
d4
16.7%
e4
16.7%
m4
16.7%
n2
8.3%
S2
8.3%
p2
8.3%
s2
8.3%
i2
8.3%
W2
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII412
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3113
27.4%
180
19.4%
.43
 
10.4%
636
 
8.7%
527
 
6.6%
724
 
5.8%
219
 
4.6%
415
 
3.6%
811
 
2.7%
95
 
1.2%
Other values (14)39
 
9.5%

Timestamp
Categorical

HIGH CARDINALITY
HIGH CORRELATION
MISSING
UNIFORM

Distinct72
Distinct (%)94.7%
Missing2
Missing (%)2.6%
Memory size752.0 B
4/7/2019 15:19
 
2
4/7/2019 15:17
 
2
4/2/2019 12:59
 
2
4/6/2019 16:58
 
2
4/10/2019 13:35
 
1
Other values (67)
67 

Length

Max length18
Median length14
Mean length14.31578947
Min length9

Characters and Unicode

Total characters1088
Distinct characters22
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)89.5%

Sample

1st row4/7/2019 15:19
2nd row4/7/2019 15:19
3rd row4/7/2019 16:55
4th row4/7/2019 14:53
5th row4/7/2019 14:59

Common Values

ValueCountFrequency (%)
4/7/2019 15:192
 
2.6%
4/7/2019 15:172
 
2.6%
4/2/2019 12:592
 
2.6%
4/6/2019 16:582
 
2.6%
4/10/2019 13:351
 
1.3%
4/10/2019 10:121
 
1.3%
Timestamp1
 
1.3%
4/10/2019 8:311
 
1.3%
4/10/2019 8:341
 
1.3%
4/10/2019 8:421
 
1.3%
Other values (62)62
79.5%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:55.090945image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
4/10/201930
20.0%
4/7/201921
 
14.0%
4/6/20195
 
3.3%
4/1/20194
 
2.7%
4/5/20194
 
2.7%
3/21/20193
 
2.0%
4/2/20193
 
2.0%
16:582
 
1.3%
13:352
 
1.3%
timestamp2
 
1.3%
Other values (69)74
49.3%

Most occurring characters

ValueCountFrequency (%)
1211
19.4%
/148
13.6%
0120
11.0%
2110
10.1%
4101
9.3%
986
7.9%
:77
 
7.1%
74
 
6.8%
540
 
3.7%
335
 
3.2%
Other values (12)86
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number771
70.9%
Other Punctuation225
 
20.7%
Space Separator74
 
6.8%
Lowercase Letter15
 
1.4%
Uppercase Letter3
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1211
27.4%
0120
15.6%
2110
14.3%
4101
13.1%
986
11.2%
540
 
5.2%
335
 
4.5%
733
 
4.3%
626
 
3.4%
89
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
m4
26.7%
i2
13.3%
e2
13.3%
t2
13.3%
a2
13.3%
p2
13.3%
s1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
/148
65.8%
:77
34.2%
Uppercase Letter
ValueCountFrequency (%)
T2
66.7%
S1
33.3%
Space Separator
ValueCountFrequency (%)
74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1070
98.3%
Latin18
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1211
19.7%
/148
13.8%
0120
11.2%
2110
10.3%
4101
9.4%
986
8.0%
:77
 
7.2%
74
 
6.9%
540
 
3.7%
335
 
3.3%
Other values (3)68
 
6.4%
Latin
ValueCountFrequency (%)
m4
22.2%
T2
11.1%
i2
11.1%
e2
11.1%
t2
11.1%
a2
11.1%
p2
11.1%
s1
 
5.6%
S1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII1088
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1211
19.4%
/148
13.6%
0120
11.0%
2110
10.1%
4101
9.3%
986
7.9%
:77
 
7.1%
74
 
6.8%
540
 
3.7%
335
 
3.2%
Other values (12)86
7.9%

Room name and code
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct20
Distinct (%)26.3%
Missing2
Missing (%)2.6%
Memory size752.0 B
STU211
31 
lobby
STU203
STU301
CL302
 
3
Other values (15)
23 

Length

Max length18
Median length6
Mean length6
Min length5

Characters and Unicode

Total characters456
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)11.8%

Sample

1st rowSTU302
2nd rowSTU302
3rd rowSTU302
4th rowSTU207
5th rowSTU207

Common Values

ValueCountFrequency (%)
STU21131
39.7%
lobby8
 
10.3%
STU2036
 
7.7%
STU3015
 
6.4%
CL3023
 
3.8%
STU201 3
 
3.8%
STU3023
 
3.8%
LAB302 2
 
2.6%
STU2072
 
2.6%
STU3042
 
2.6%
Other values (10)11
 
14.1%

Length

2022-08-24T15:06:55.220570image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
stu21131
39.2%
lobby8
 
10.1%
stu2036
 
7.6%
stu3015
 
6.3%
stu2014
 
5.1%
stu3043
 
3.8%
cl3023
 
3.8%
stu3023
 
3.8%
room2
 
2.5%
ad3162
 
2.5%
Other values (10)12
 
15.2%

Most occurring characters

ValueCountFrequency (%)
177
16.9%
S55
12.1%
U55
12.1%
T55
12.1%
252
11.4%
031
6.8%
327
 
5.9%
b16
 
3.5%
o13
 
2.9%
10
 
2.2%
Other values (19)65
14.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number196
43.0%
Uppercase Letter193
42.3%
Lowercase Letter57
 
12.5%
Space Separator10
 
2.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S55
28.5%
U55
28.5%
T55
28.5%
L9
 
4.7%
C6
 
3.1%
A4
 
2.1%
B2
 
1.0%
D2
 
1.0%
R2
 
1.0%
E2
 
1.0%
Lowercase Letter
ValueCountFrequency (%)
b16
28.1%
o13
22.8%
l8
14.0%
y8
14.0%
m3
 
5.3%
n2
 
3.5%
a2
 
3.5%
e2
 
3.5%
d2
 
3.5%
c1
 
1.8%
Decimal Number
ValueCountFrequency (%)
177
39.3%
252
26.5%
031
15.8%
327
 
13.8%
44
 
2.0%
63
 
1.5%
72
 
1.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin250
54.8%
Common206
45.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
S55
22.0%
U55
22.0%
T55
22.0%
b16
 
6.4%
o13
 
5.2%
L9
 
3.6%
l8
 
3.2%
y8
 
3.2%
C6
 
2.4%
A4
 
1.6%
Other values (11)21
 
8.4%
Common
ValueCountFrequency (%)
177
37.4%
252
25.2%
031
15.0%
327
 
13.1%
10
 
4.9%
44
 
1.9%
63
 
1.5%
72
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII456
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
177
16.9%
S55
12.1%
U55
12.1%
T55
12.1%
252
11.4%
031
6.8%
327
 
5.9%
b16
 
3.5%
o13
 
2.9%
10
 
2.2%
Other values (19)65
14.3%

Gender
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)2.6%
Missing2
Missing (%)2.6%
Memory size752.0 B
Male
74 
Gender
 
2

Length

Max length7
Median length4
Mean length4.078947368
Min length4

Characters and Unicode

Total characters310
Distinct characters9
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMale
2nd rowMale
3rd rowMale
4th rowMale
5th rowMale

Common Values

ValueCountFrequency (%)
Male74
94.9%
Gender 2
 
2.6%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:55.354783image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:55.488315image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
male74
97.4%
gender2
 
2.6%

Most occurring characters

ValueCountFrequency (%)
e78
25.2%
M74
23.9%
a74
23.9%
l74
23.9%
G2
 
0.6%
n2
 
0.6%
d2
 
0.6%
r2
 
0.6%
2
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter232
74.8%
Uppercase Letter76
 
24.5%
Space Separator2
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e78
33.6%
a74
31.9%
l74
31.9%
n2
 
0.9%
d2
 
0.9%
r2
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
M74
97.4%
G2
 
2.6%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin308
99.4%
Common2
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e78
25.3%
M74
24.0%
a74
24.0%
l74
24.0%
G2
 
0.6%
n2
 
0.6%
d2
 
0.6%
r2
 
0.6%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII310
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e78
25.2%
M74
23.9%
a74
23.9%
l74
23.9%
G2
 
0.6%
n2
 
0.6%
d2
 
0.6%
r2
 
0.6%
2
 
0.6%

Occupation
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)5.3%
Missing2
Missing (%)2.6%
Memory size752.0 B
Occ01
51 
Occ02
21 
Occ03
 
2
Occupation
 
2

Length

Max length11
Median length5
Mean length5.157894737
Min length5

Characters and Unicode

Total characters392
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOcc02
2nd rowOcc01
3rd rowOcc01
4th rowOcc01
5th rowOcc01

Common Values

ValueCountFrequency (%)
Occ0151
65.4%
Occ0221
26.9%
Occ032
 
2.6%
Occupation 2
 
2.6%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:55.599720image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:55.739980image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
occ0151
67.1%
occ0221
27.6%
occ032
 
2.6%
occupation2
 
2.6%

Most occurring characters

ValueCountFrequency (%)
c152
38.8%
O76
19.4%
074
18.9%
151
 
13.0%
221
 
5.4%
32
 
0.5%
u2
 
0.5%
p2
 
0.5%
a2
 
0.5%
t2
 
0.5%
Other values (4)8
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter166
42.3%
Decimal Number148
37.8%
Uppercase Letter76
19.4%
Space Separator2
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c152
91.6%
u2
 
1.2%
p2
 
1.2%
a2
 
1.2%
t2
 
1.2%
i2
 
1.2%
o2
 
1.2%
n2
 
1.2%
Decimal Number
ValueCountFrequency (%)
074
50.0%
151
34.5%
221
 
14.2%
32
 
1.4%
Uppercase Letter
ValueCountFrequency (%)
O76
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin242
61.7%
Common150
38.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
c152
62.8%
O76
31.4%
u2
 
0.8%
p2
 
0.8%
a2
 
0.8%
t2
 
0.8%
i2
 
0.8%
o2
 
0.8%
n2
 
0.8%
Common
ValueCountFrequency (%)
074
49.3%
151
34.0%
221
 
14.0%
32
 
1.3%
2
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII392
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c152
38.8%
O76
19.4%
074
18.9%
151
 
13.0%
221
 
5.4%
32
 
0.5%
u2
 
0.5%
p2
 
0.5%
a2
 
0.5%
t2
 
0.5%
Other values (4)8
 
2.0%

Age
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)5.3%
Missing2
Missing (%)2.6%
Memory size752.0 B
Age01
52 
Age02
17 
Age03
 
5
Age
 
2

Length

Max length5
Median length5
Mean length4.947368421
Min length3

Characters and Unicode

Total characters376
Distinct characters7
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAge02
2nd rowAge01
3rd rowAge01
4th rowAge01
5th rowAge01

Common Values

ValueCountFrequency (%)
Age0152
66.7%
Age0217
 
21.8%
Age035
 
6.4%
Age2
 
2.6%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:55.867970image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:56.015684image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
age0152
68.4%
age0217
 
22.4%
age035
 
6.6%
age2
 
2.6%

Most occurring characters

ValueCountFrequency (%)
A76
20.2%
g76
20.2%
e76
20.2%
074
19.7%
152
13.8%
217
 
4.5%
35
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter152
40.4%
Decimal Number148
39.4%
Uppercase Letter76
20.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
074
50.0%
152
35.1%
217
 
11.5%
35
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
g76
50.0%
e76
50.0%
Uppercase Letter
ValueCountFrequency (%)
A76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin228
60.6%
Common148
39.4%

Most frequent character per script

Common
ValueCountFrequency (%)
074
50.0%
152
35.1%
217
 
11.5%
35
 
3.4%
Latin
ValueCountFrequency (%)
A76
33.3%
g76
33.3%
e76
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII376
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A76
20.2%
g76
20.2%
e76
20.2%
074
19.7%
152
13.8%
217
 
4.5%
35
 
1.3%

Height
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct7
Distinct (%)9.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
Hight04
33 
Hight03
27 
Hight05
11 
Height
 
2
Hight06
 
1
Other values (2)
 
2

Length

Max length7
Median length7
Mean length6.973684211
Min length6

Characters and Unicode

Total characters530
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)3.9%

Sample

1st rowHight04
2nd rowHight05
3rd rowHight03
4th rowHight04
5th rowHight03

Common Values

ValueCountFrequency (%)
Hight0433
42.3%
Hight0327
34.6%
Hight0511
 
14.1%
Height2
 
2.6%
Hight061
 
1.3%
Hight011
 
1.3%
Hight021
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:56.137041image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:56.286392image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
hight0433
43.4%
hight0327
35.5%
hight0511
 
14.5%
height2
 
2.6%
hight061
 
1.3%
hight011
 
1.3%
hight021
 
1.3%

Most occurring characters

ValueCountFrequency (%)
H76
14.3%
i76
14.3%
g76
14.3%
h76
14.3%
t76
14.3%
074
14.0%
433
6.2%
327
 
5.1%
511
 
2.1%
e2
 
0.4%
Other values (3)3
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter306
57.7%
Decimal Number148
27.9%
Uppercase Letter76
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
074
50.0%
433
22.3%
327
 
18.2%
511
 
7.4%
61
 
0.7%
11
 
0.7%
21
 
0.7%
Lowercase Letter
ValueCountFrequency (%)
i76
24.8%
g76
24.8%
h76
24.8%
t76
24.8%
e2
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
H76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin382
72.1%
Common148
 
27.9%

Most frequent character per script

Common
ValueCountFrequency (%)
074
50.0%
433
22.3%
327
 
18.2%
511
 
7.4%
61
 
0.7%
11
 
0.7%
21
 
0.7%
Latin
ValueCountFrequency (%)
H76
19.9%
i76
19.9%
g76
19.9%
h76
19.9%
t76
19.9%
e2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII530
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
H76
14.3%
i76
14.3%
g76
14.3%
h76
14.3%
t76
14.3%
074
14.0%
433
6.2%
327
 
5.1%
511
 
2.1%
e2
 
0.4%
Other values (3)3
 
0.6%

Weight
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct8
Distinct (%)10.5%
Missing2
Missing (%)2.6%
Memory size752.0 B
Wieg02
20 
Wieg03
15 
Wieg01
14 
Wieg05
13 
Wieg04
Other values (3)

Length

Max length9
Median length6
Mean length6.039473684
Min length6

Characters and Unicode

Total characters459
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st rowWieg03
2nd rowWieg04
3rd rowWieg02
4th rowWieg03
5th rowWieg02

Common Values

ValueCountFrequency (%)
Wieg0220
25.6%
Wieg0315
19.2%
Wieg0114
17.9%
Wieg0513
16.7%
Wieg049
11.5%
Wieg063
 
3.8%
Wieght. 1
 
1.3%
Wieght1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:56.426263image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:56.583447image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
wieg0220
26.3%
wieg0315
19.7%
wieg0114
18.4%
wieg0513
17.1%
wieg049
11.8%
wieg063
 
3.9%
wieght2
 
2.6%

Most occurring characters

ValueCountFrequency (%)
W76
16.6%
i76
16.6%
e76
16.6%
g76
16.6%
074
16.1%
220
 
4.4%
315
 
3.3%
114
 
3.1%
513
 
2.8%
49
 
2.0%
Other values (5)10
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter232
50.5%
Decimal Number148
32.2%
Uppercase Letter76
 
16.6%
Space Separator2
 
0.4%
Other Punctuation1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
074
50.0%
220
 
13.5%
315
 
10.1%
114
 
9.5%
513
 
8.8%
49
 
6.1%
63
 
2.0%
Lowercase Letter
ValueCountFrequency (%)
i76
32.8%
e76
32.8%
g76
32.8%
h2
 
0.9%
t2
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
W76
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
.1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin308
67.1%
Common151
32.9%

Most frequent character per script

Common
ValueCountFrequency (%)
074
49.0%
220
 
13.2%
315
 
9.9%
114
 
9.3%
513
 
8.6%
49
 
6.0%
63
 
2.0%
2
 
1.3%
.1
 
0.7%
Latin
ValueCountFrequency (%)
W76
24.7%
i76
24.7%
e76
24.7%
g76
24.7%
h2
 
0.6%
t2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII459
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
W76
16.6%
i76
16.6%
e76
16.6%
g76
16.6%
074
16.1%
220
 
4.4%
315
 
3.3%
114
 
3.1%
513
 
2.8%
49
 
2.0%
Other values (5)10
 
2.2%

Your Activity
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct8
Distinct (%)10.5%
Missing2
Missing (%)2.6%
Memory size752.0 B
Walking
24 
Working
24 
Running
Stall
ClimbingStairs
Other values (3)

Length

Max length14
Median length7
Mean length7.302631579
Min length5

Characters and Unicode

Total characters555
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st rowWalking
2nd rowWalking
3rd rowWalking
4th rowWalking
5th rowRunning

Common Values

ValueCountFrequency (%)
Walking24
30.8%
Working24
30.8%
Running9
 
11.5%
Stall9
 
11.5%
ClimbingStairs4
 
5.1%
Sleeping4
 
5.1%
Your Activity 1
 
1.3%
Activity 1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:56.729039image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:56.877950image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
walking24
31.2%
working24
31.2%
running9
 
11.7%
stall9
 
11.7%
climbingstairs4
 
5.2%
sleeping4
 
5.2%
activity2
 
2.6%
your1
 
1.3%

Most occurring characters

ValueCountFrequency (%)
n83
15.0%
i77
13.9%
g65
11.7%
l50
9.0%
W48
8.6%
k48
8.6%
a37
6.7%
r29
 
5.2%
o25
 
4.5%
S17
 
3.1%
Other values (15)76
13.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter471
84.9%
Uppercase Letter81
 
14.6%
Space Separator3
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n83
17.6%
i77
16.3%
g65
13.8%
l50
10.6%
k48
10.2%
a37
7.9%
r29
 
6.2%
o25
 
5.3%
t17
 
3.6%
u10
 
2.1%
Other values (8)30
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
W48
59.3%
S17
 
21.0%
R9
 
11.1%
C4
 
4.9%
A2
 
2.5%
Y1
 
1.2%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin552
99.5%
Common3
 
0.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
n83
15.0%
i77
13.9%
g65
11.8%
l50
9.1%
W48
8.7%
k48
8.7%
a37
6.7%
r29
 
5.3%
o25
 
4.5%
S17
 
3.1%
Other values (14)73
13.2%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII555
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n83
15.0%
i77
13.9%
g65
11.7%
l50
9.0%
W48
8.6%
k48
8.6%
a37
6.7%
r29
 
5.2%
o25
 
4.5%
S17
 
3.1%
Other values (15)76
13.7%

Clothing
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct16
Distinct (%)21.1%
Missing2
Missing (%)2.6%
Memory size752.0 B
Dress_364
26 
Dress_192
11 
Dress_220
Dress_213
Dress_150
Other values (11)
18 

Length

Max length13
Median length9
Mean length9
Min length8

Characters and Unicode

Total characters684
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)9.2%

Sample

1st rowDress_364
2nd rowDress_213
3rd rowDress_364
4th rowDress_192
5th rowDress_99

Common Values

ValueCountFrequency (%)
Dress_36426
33.3%
Dress_19211
14.1%
Dress_2208
 
10.3%
Dress_2138
 
10.3%
Dress_1505
 
6.4%
Dress_3655
 
6.4%
Dress_992
 
2.6%
Dress_1942
 
2.6%
Dress_2072
 
2.6%
Dress_941
 
1.3%
Other values (6)6
 
7.7%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:57.199432image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
dress_36426
33.3%
dress_19211
14.1%
dress_2208
 
10.3%
dress_2138
 
10.3%
dress_1505
 
6.4%
dress_3655
 
6.4%
type2
 
2.6%
dress_2072
 
2.6%
dress_1942
 
2.6%
dress_992
 
2.6%
Other values (7)7
 
9.0%

Most occurring characters

ValueCountFrequency (%)
s148
21.6%
e76
11.1%
D74
10.8%
r74
10.8%
_74
10.8%
241
 
6.0%
339
 
5.7%
632
 
4.7%
429
 
4.2%
127
 
3.9%
Other values (17)70
10.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter313
45.8%
Decimal Number217
31.7%
Uppercase Letter78
 
11.4%
Connector Punctuation74
 
10.8%
Space Separator2
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s148
47.3%
e76
24.3%
r74
23.6%
l2
 
0.6%
o2
 
0.6%
t2
 
0.6%
h2
 
0.6%
y2
 
0.6%
p2
 
0.6%
i1
 
0.3%
Other values (2)2
 
0.6%
Decimal Number
ValueCountFrequency (%)
241
18.9%
339
18.0%
632
14.7%
429
13.4%
127
12.4%
918
8.3%
016
 
7.4%
511
 
5.1%
73
 
1.4%
81
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
D74
94.9%
C2
 
2.6%
T2
 
2.6%
Connector Punctuation
ValueCountFrequency (%)
_74
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin391
57.2%
Common293
42.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
s148
37.9%
e76
19.4%
D74
18.9%
r74
18.9%
C2
 
0.5%
l2
 
0.5%
o2
 
0.5%
t2
 
0.5%
h2
 
0.5%
T2
 
0.5%
Other values (5)7
 
1.8%
Common
ValueCountFrequency (%)
_74
25.3%
241
14.0%
339
13.3%
632
10.9%
429
 
9.9%
127
 
9.2%
918
 
6.1%
016
 
5.5%
511
 
3.8%
73
 
1.0%
Other values (2)3
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII684
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s148
21.6%
e76
11.1%
D74
10.8%
r74
10.8%
_74
10.8%
241
 
6.0%
339
 
5.7%
632
 
4.7%
429
 
4.2%
127
 
3.9%
Other values (17)70
10.2%

How long do you spend in the building during the day
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct10
Distinct (%)13.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
Period_08
22 
Period_07
12 
Period_03
11 
Period_04
Period_05
Other values (5)
15 

Length

Max length53
Median length9
Mean length9.697368421
Min length9

Characters and Unicode

Total characters737
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st rowPeriod_08
2nd rowPeriod_08
3rd rowPeriod_10
4th rowPeriod_08
5th rowPeriod_10

Common Values

ValueCountFrequency (%)
Period_0822
28.2%
Period_0712
15.4%
Period_0311
14.1%
Period_049
11.5%
Period_057
 
9.0%
Period_095
 
6.4%
Period_104
 
5.1%
Period_024
 
5.1%
How long do you spend in the building during the day?1
 
1.3%
Time in the office1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:57.331805image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:57.491146image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
period_0822
24.7%
period_0712
13.5%
period_0311
12.4%
period_049
10.1%
period_057
 
7.9%
period_095
 
5.6%
period_104
 
4.5%
period_024
 
4.5%
the3
 
3.4%
in2
 
2.2%
Other values (10)10
11.2%

Most occurring characters

ValueCountFrequency (%)
i81
11.0%
e80
10.9%
o79
10.7%
d79
10.7%
r75
10.2%
P74
10.0%
_74
10.0%
074
10.0%
822
 
3.0%
13
 
1.8%
Other values (25)86
11.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter425
57.7%
Decimal Number148
 
20.1%
Uppercase Letter76
 
10.3%
Connector Punctuation74
 
10.0%
Space Separator13
 
1.8%
Other Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i81
19.1%
e80
18.8%
o79
18.6%
d79
18.6%
r75
17.6%
n6
 
1.4%
g3
 
0.7%
u3
 
0.7%
t3
 
0.7%
h3
 
0.7%
Other values (10)13
 
3.1%
Decimal Number
ValueCountFrequency (%)
074
50.0%
822
 
14.9%
712
 
8.1%
311
 
7.4%
49
 
6.1%
57
 
4.7%
95
 
3.4%
14
 
2.7%
24
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
P74
97.4%
T1
 
1.3%
H1
 
1.3%
Connector Punctuation
ValueCountFrequency (%)
_74
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin501
68.0%
Common236
32.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i81
16.2%
e80
16.0%
o79
15.8%
d79
15.8%
r75
15.0%
P74
14.8%
n6
 
1.2%
g3
 
0.6%
u3
 
0.6%
t3
 
0.6%
Other values (13)18
 
3.6%
Common
ValueCountFrequency (%)
_74
31.4%
074
31.4%
822
 
9.3%
13
 
5.5%
712
 
5.1%
311
 
4.7%
49
 
3.8%
57
 
3.0%
95
 
2.1%
14
 
1.7%
Other values (2)5
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII737
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i81
11.0%
e80
10.9%
o79
10.7%
d79
10.7%
r75
10.2%
P74
10.0%
_74
10.0%
074
10.0%
822
 
3.0%
13
 
1.8%
Other values (25)86
11.7%

How long have you (worked-studied) in this building
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct12
Distinct (%)15.8%
Missing2
Missing (%)2.6%
Memory size752.0 B
Stu-Period_02
17 
Stu-Period_03
13 
4
13 
2
3
Other values (7)
17 

Length

Max length44
Median length13
Mean length8.894736842
Min length1

Characters and Unicode

Total characters676
Distinct characters40
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)3.9%

Sample

1st rowStu-Period_01
2nd rowStu-Period_06
3rd rowStu-Period_03
4th rowStu-Period_04
5th rowStu-Period_03

Common Values

ValueCountFrequency (%)
Stu-Period_0217
21.8%
Stu-Period_0313
16.7%
413
16.7%
28
10.3%
38
10.3%
Stu-Period_015
 
6.4%
Stu-Period_045
 
6.4%
Stu-Period_062
 
2.6%
12
 
2.6%
How long have you (worked) in this building?1
 
1.3%
Other values (2)2
 
2.6%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:57.649546image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
stu-period_0217
19.5%
413
14.9%
stu-period_0313
14.9%
28
9.2%
38
9.2%
stu-period_015
 
5.7%
stu-period_045
 
5.7%
stu-period_062
 
2.3%
12
 
2.3%
building1
 
1.1%
Other values (13)13
14.9%

Most occurring characters

ValueCountFrequency (%)
e52
 
7.7%
r50
 
7.4%
t49
 
7.2%
o49
 
7.2%
u48
 
7.1%
i47
 
7.0%
d46
 
6.8%
S43
 
6.4%
043
 
6.4%
_43
 
6.4%
Other values (30)206
30.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter370
54.7%
Decimal Number117
 
17.3%
Uppercase Letter88
 
13.0%
Connector Punctuation43
 
6.4%
Dash Punctuation43
 
6.4%
Space Separator11
 
1.6%
Other Punctuation2
 
0.3%
Close Punctuation1
 
0.1%
Open Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e52
14.1%
r50
13.5%
t49
13.2%
o49
13.2%
u48
13.0%
i47
12.7%
d46
12.4%
n5
 
1.4%
a3
 
0.8%
h3
 
0.8%
Other values (12)18
 
4.9%
Decimal Number
ValueCountFrequency (%)
043
36.8%
225
21.4%
321
17.9%
418
15.4%
17
 
6.0%
62
 
1.7%
51
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
S43
48.9%
P43
48.9%
C1
 
1.1%
H1
 
1.1%
Other Punctuation
ValueCountFrequency (%)
?1
50.0%
.1
50.0%
Connector Punctuation
ValueCountFrequency (%)
_43
100.0%
Dash Punctuation
ValueCountFrequency (%)
-43
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin458
67.8%
Common218
32.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e52
11.4%
r50
10.9%
t49
10.7%
o49
10.7%
u48
10.5%
i47
10.3%
d46
10.0%
S43
9.4%
P43
9.4%
n5
 
1.1%
Other values (16)26
5.7%
Common
ValueCountFrequency (%)
043
19.7%
_43
19.7%
-43
19.7%
225
11.5%
321
9.6%
418
8.3%
11
 
5.0%
17
 
3.2%
62
 
0.9%
?1
 
0.5%
Other values (4)4
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e52
 
7.7%
r50
 
7.4%
t49
 
7.2%
o49
 
7.2%
u48
 
7.1%
i47
 
7.0%
d46
 
6.8%
S43
 
6.4%
043
 
6.4%
_43
 
6.4%
Other values (30)206
30.5%

In average day how much time do you spend in the [Office ]
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct10
Distinct (%)13.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
Period_01
21 
3
13 
Period_07
10 
4
10 
2
Other values (5)
14 

Length

Max length58
Median length9
Mean length6.736842105
Min length1

Characters and Unicode

Total characters512
Distinct characters36
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)3.9%

Sample

1st rowPeriod_12
2nd rowPeriod_12
3rd rowPeriod_01
4th rowPeriod_01
5th rowPeriod_11

Common Values

ValueCountFrequency (%)
Period_0121
26.9%
313
16.7%
Period_0710
12.8%
410
12.8%
28
 
10.3%
Period_116
 
7.7%
Period_125
 
6.4%
In average day how much time do you spend in the [Office]?1
 
1.3%
Period_081
 
1.3%
The Current temperature in the room 1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:57.775070image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:57.939577image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
period_0121
22.8%
313
14.1%
period_0710
10.9%
410
10.9%
28
 
8.7%
period_116
 
6.5%
period_125
 
5.4%
in3
 
3.3%
the3
 
3.3%
spend1
 
1.1%
Other values (12)12
13.0%

Most occurring characters

ValueCountFrequency (%)
e55
10.7%
r49
9.6%
o48
9.4%
i47
9.2%
d46
9.0%
P43
8.4%
_43
8.4%
138
7.4%
032
 
6.2%
17
 
3.3%
Other values (26)94
18.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter285
55.7%
Decimal Number117
22.9%
Uppercase Letter47
 
9.2%
Connector Punctuation43
 
8.4%
Space Separator17
 
3.3%
Other Punctuation1
 
0.2%
Close Punctuation1
 
0.2%
Open Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e55
19.3%
r49
17.2%
o48
16.8%
i47
16.5%
d46
16.1%
t6
 
2.1%
h5
 
1.8%
n5
 
1.8%
a4
 
1.4%
m4
 
1.4%
Other values (9)16
 
5.6%
Decimal Number
ValueCountFrequency (%)
138
32.5%
032
27.4%
313
 
11.1%
213
 
11.1%
710
 
8.5%
410
 
8.5%
81
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
P43
91.5%
O1
 
2.1%
T1
 
2.1%
I1
 
2.1%
C1
 
2.1%
Connector Punctuation
ValueCountFrequency (%)
_43
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%
Close Punctuation
ValueCountFrequency (%)
]1
100.0%
Open Punctuation
ValueCountFrequency (%)
[1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin332
64.8%
Common180
35.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e55
16.6%
r49
14.8%
o48
14.5%
i47
14.2%
d46
13.9%
P43
13.0%
t6
 
1.8%
h5
 
1.5%
n5
 
1.5%
a4
 
1.2%
Other values (14)24
7.2%
Common
ValueCountFrequency (%)
_43
23.9%
138
21.1%
032
17.8%
17
 
9.4%
313
 
7.2%
213
 
7.2%
710
 
5.6%
410
 
5.6%
81
 
0.6%
?1
 
0.6%
Other values (2)2
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII512
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e55
10.7%
r49
9.6%
o48
9.4%
i47
9.2%
d46
9.0%
P43
8.4%
_43
8.4%
138
7.4%
032
 
6.2%
17
 
3.3%
Other values (26)94
18.4%

In average day how much time do you spend in the [Lecture room ]
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct10
Distinct (%)13.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
No
26 
Period_12
23 
Period_11
Period_07
Period_01
Other values (5)

Length

Max length64
Median length9
Mean length7.289473684
Min length2

Characters and Unicode

Total characters554
Distinct characters37
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st rowPeriod_12
2nd rowPeriod_01
3rd rowPeriod_08
4th rowPeriod_12
5th rowPeriod_12

Common Values

ValueCountFrequency (%)
No26
33.3%
Period_1223
29.5%
Period_118
 
10.3%
Period_077
 
9.0%
Period_013
 
3.8%
Yes3
 
3.8%
Period_082
 
2.6%
Maybe2
 
2.6%
In average day how much time do you spend in the [Lecture room]?1
 
1.3%
Distraction from outside noise? 1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:58.110997image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:58.279068image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no26
28.6%
period_1223
25.3%
period_118
 
8.8%
period_077
 
7.7%
period_013
 
3.3%
yes3
 
3.3%
period_082
 
2.2%
maybe2
 
2.2%
in2
 
2.2%
spend1
 
1.1%
Other values (14)14
15.4%

Most occurring characters

ValueCountFrequency (%)
o78
14.1%
e57
10.3%
i49
8.8%
r48
8.7%
d47
8.5%
P43
7.8%
_43
7.8%
142
7.6%
N26
 
4.7%
223
 
4.2%
Other values (27)98
17.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter328
59.2%
Decimal Number86
 
15.5%
Uppercase Letter77
 
13.9%
Connector Punctuation43
 
7.8%
Space Separator16
 
2.9%
Other Punctuation2
 
0.4%
Open Punctuation1
 
0.2%
Close Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o78
23.8%
e57
17.4%
i49
14.9%
r48
14.6%
d47
14.3%
s7
 
2.1%
t6
 
1.8%
a6
 
1.8%
n5
 
1.5%
u4
 
1.2%
Other values (10)21
 
6.4%
Uppercase Letter
ValueCountFrequency (%)
P43
55.8%
N26
33.8%
Y3
 
3.9%
M2
 
2.6%
I1
 
1.3%
L1
 
1.3%
D1
 
1.3%
Decimal Number
ValueCountFrequency (%)
142
48.8%
223
26.7%
012
 
14.0%
77
 
8.1%
82
 
2.3%
Connector Punctuation
ValueCountFrequency (%)
_43
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
?2
100.0%
Open Punctuation
ValueCountFrequency (%)
[1
100.0%
Close Punctuation
ValueCountFrequency (%)
]1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin405
73.1%
Common149
 
26.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o78
19.3%
e57
14.1%
i49
12.1%
r48
11.9%
d47
11.6%
P43
10.6%
N26
 
6.4%
s7
 
1.7%
t6
 
1.5%
a6
 
1.5%
Other values (17)38
9.4%
Common
ValueCountFrequency (%)
_43
28.9%
142
28.2%
223
15.4%
16
 
10.7%
012
 
8.1%
77
 
4.7%
?2
 
1.3%
82
 
1.3%
[1
 
0.7%
]1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII554
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o78
14.1%
e57
10.3%
i49
8.8%
r48
8.7%
d47
8.5%
P43
7.8%
_43
7.8%
142
7.6%
N26
 
4.7%
223
 
4.2%
Other values (27)98
17.7%

In average day how much time do you spend in the [laboratory ]
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct9
Distinct (%)11.8%
Missing2
Missing (%)2.6%
Memory size752.0 B
Period_01
26 
No
24 
Period_11
11 
Period_12
Yes
Other values (4)

Length

Max length62
Median length9
Mean length7.434210526
Min length2

Characters and Unicode

Total characters565
Distinct characters37
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st rowPeriod_01
2nd rowPeriod_01
3rd rowPeriod_11
4th rowPeriod_01
5th rowPeriod_11

Common Values

ValueCountFrequency (%)
Period_0126
33.3%
No24
30.8%
Period_1111
14.1%
Period_124
 
5.1%
Yes4
 
5.1%
Maybe3
 
3.8%
Period_072
 
2.6%
In average day how much time do you spend in the [laboratory]?1
 
1.3%
Distraction from background machine noise1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:58.456275image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:58.618016image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
period_0126
28.6%
no24
26.4%
period_1111
12.1%
period_124
 
4.4%
yes4
 
4.4%
maybe3
 
3.3%
period_072
 
2.2%
in2
 
2.2%
spend1
 
1.1%
machine1
 
1.1%
Other values (13)13
14.3%

Most occurring characters

ValueCountFrequency (%)
o76
13.5%
e57
10.1%
152
9.2%
r49
8.7%
i49
8.7%
d47
8.3%
P43
7.6%
_43
7.6%
028
 
5.0%
N24
 
4.2%
Other values (27)97
17.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter342
60.5%
Decimal Number86
 
15.2%
Uppercase Letter76
 
13.5%
Connector Punctuation43
 
7.6%
Space Separator15
 
2.7%
Other Punctuation1
 
0.2%
Close Punctuation1
 
0.2%
Open Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o76
22.2%
e57
16.7%
r49
14.3%
i49
14.3%
d47
13.7%
a11
 
3.2%
n7
 
2.0%
s7
 
2.0%
y6
 
1.8%
b5
 
1.5%
Other values (12)28
 
8.2%
Uppercase Letter
ValueCountFrequency (%)
P43
56.6%
N24
31.6%
Y4
 
5.3%
M3
 
3.9%
D1
 
1.3%
I1
 
1.3%
Decimal Number
ValueCountFrequency (%)
152
60.5%
028
32.6%
24
 
4.7%
72
 
2.3%
Connector Punctuation
ValueCountFrequency (%)
_43
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%
Close Punctuation
ValueCountFrequency (%)
]1
100.0%
Open Punctuation
ValueCountFrequency (%)
[1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin418
74.0%
Common147
 
26.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o76
18.2%
e57
13.6%
r49
11.7%
i49
11.7%
d47
11.2%
P43
10.3%
N24
 
5.7%
a11
 
2.6%
n7
 
1.7%
s7
 
1.7%
Other values (18)48
11.5%
Common
ValueCountFrequency (%)
152
35.4%
_43
29.3%
028
19.0%
15
 
10.2%
24
 
2.7%
72
 
1.4%
?1
 
0.7%
]1
 
0.7%
[1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII565
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o76
13.5%
e57
10.1%
152
9.2%
r49
8.7%
i49
8.7%
d47
8.3%
P43
7.6%
_43
7.6%
028
 
5.0%
N24
 
4.2%
Other values (27)97
17.2%

In average day how much time do you spend in the [Studio Design]
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct11
Distinct (%)14.5%
Missing2
Missing (%)2.6%
Memory size752.0 B
Yes
25 
Period_12
15 
Period_07
12 
Period_11
No
Other values (6)
14 

Length

Max length65
Median length9
Mean length7.513157895
Min length2

Characters and Unicode

Total characters571
Distinct characters39
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)3.9%

Sample

1st rowPeriod_12
2nd rowPeriod_07
3rd rowPeriod_13
4th rowPeriod_07
5th rowPeriod_12

Common Values

ValueCountFrequency (%)
Yes25
32.1%
Period_1215
19.2%
Period_0712
15.4%
Period_115
 
6.4%
No5
 
6.4%
Period_134
 
5.1%
Period_014
 
5.1%
Period_083
 
3.8%
In average day how much time do you spend in the [Studio Design]?1
 
1.3%
Distraction from people noise1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:58.778847image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
yes25
27.5%
period_1215
16.5%
period_0712
13.2%
period_115
 
5.5%
no5
 
5.5%
period_134
 
4.4%
period_014
 
4.4%
period_083
 
3.3%
in2
 
2.2%
the1
 
1.1%
Other values (15)15
16.5%

Most occurring characters

ValueCountFrequency (%)
e78
13.7%
o56
9.8%
i50
8.8%
d47
 
8.2%
r46
 
8.1%
P43
 
7.5%
_43
 
7.5%
133
 
5.8%
s29
 
5.1%
Y25
 
4.4%
Other values (29)121
21.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter346
60.6%
Decimal Number86
 
15.1%
Uppercase Letter78
 
13.7%
Connector Punctuation43
 
7.5%
Space Separator15
 
2.6%
Close Punctuation1
 
0.2%
Other Punctuation1
 
0.2%
Open Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e78
22.5%
o56
16.2%
i50
14.5%
d47
13.6%
r46
13.3%
s29
 
8.4%
n6
 
1.7%
t5
 
1.4%
a5
 
1.4%
y3
 
0.9%
Other values (11)21
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
P43
55.1%
Y25
32.1%
N5
 
6.4%
D2
 
2.6%
M1
 
1.3%
I1
 
1.3%
S1
 
1.3%
Decimal Number
ValueCountFrequency (%)
133
38.4%
019
22.1%
215
17.4%
712
 
14.0%
34
 
4.7%
83
 
3.5%
Connector Punctuation
ValueCountFrequency (%)
_43
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
]1
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%
Open Punctuation
ValueCountFrequency (%)
[1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin424
74.3%
Common147
 
25.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e78
18.4%
o56
13.2%
i50
11.8%
d47
11.1%
r46
10.8%
P43
10.1%
s29
 
6.8%
Y25
 
5.9%
n6
 
1.4%
t5
 
1.2%
Other values (18)39
9.2%
Common
ValueCountFrequency (%)
_43
29.3%
133
22.4%
019
12.9%
215
 
10.2%
15
 
10.2%
712
 
8.2%
34
 
2.7%
83
 
2.0%
]1
 
0.7%
?1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII571
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e78
13.7%
o56
9.8%
i50
8.8%
d47
 
8.2%
r46
 
8.1%
P43
 
7.5%
_43
 
7.5%
133
 
5.8%
s29
 
5.1%
Y25
 
4.4%
Other values (29)121
21.2%

In average day how much time do you spend in the [Cafeteria ]
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct10
Distinct (%)13.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
Period_01
25 
Period_11
17 
3
12 
4
2
Other values (5)

Length

Max length61
Median length9
Mean length6.736842105
Min length1

Characters and Unicode

Total characters512
Distinct characters36
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)3.9%

Sample

1st rowPeriod_11
2nd rowPeriod_01
3rd rowPeriod_11
4th rowPeriod_11
5th rowPeriod_11

Common Values

ValueCountFrequency (%)
Period_0125
32.1%
Period_1117
21.8%
312
15.4%
48
 
10.3%
26
 
7.7%
13
 
3.8%
52
 
2.6%
In average day how much time do you spend in the [Cafeteria]?1
 
1.3%
Period_121
 
1.3%
Comfort Under current noise Level1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:58.917576image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:59.082325image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
period_0125
27.5%
period_1117
18.7%
312
13.2%
48
 
8.8%
26
 
6.6%
13
 
3.3%
52
 
2.2%
in2
 
2.2%
the1
 
1.1%
noise1
 
1.1%
Other values (14)14
15.4%

Most occurring characters

ValueCountFrequency (%)
163
12.3%
e55
10.7%
r49
9.6%
o49
9.6%
i47
9.2%
d47
9.2%
P43
8.4%
_43
8.4%
025
 
4.9%
15
 
2.9%
Other values (26)76
14.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter286
55.9%
Decimal Number117
22.9%
Uppercase Letter48
 
9.4%
Connector Punctuation43
 
8.4%
Space Separator15
 
2.9%
Other Punctuation1
 
0.2%
Close Punctuation1
 
0.2%
Open Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e55
19.2%
r49
17.1%
o49
17.1%
i47
16.4%
d47
16.4%
n6
 
2.1%
t5
 
1.7%
a5
 
1.7%
u3
 
1.0%
m3
 
1.0%
Other values (10)17
 
5.9%
Decimal Number
ValueCountFrequency (%)
163
53.8%
025
 
21.4%
312
 
10.3%
48
 
6.8%
27
 
6.0%
52
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
P43
89.6%
C2
 
4.2%
U1
 
2.1%
L1
 
2.1%
I1
 
2.1%
Connector Punctuation
ValueCountFrequency (%)
_43
100.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%
Close Punctuation
ValueCountFrequency (%)
]1
100.0%
Open Punctuation
ValueCountFrequency (%)
[1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin334
65.2%
Common178
34.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e55
16.5%
r49
14.7%
o49
14.7%
i47
14.1%
d47
14.1%
P43
12.9%
n6
 
1.8%
t5
 
1.5%
a5
 
1.5%
u3
 
0.9%
Other values (15)25
7.5%
Common
ValueCountFrequency (%)
163
35.4%
_43
24.2%
025
 
14.0%
15
 
8.4%
312
 
6.7%
48
 
4.5%
27
 
3.9%
52
 
1.1%
?1
 
0.6%
]1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII512
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
163
12.3%
e55
10.7%
r49
9.6%
o49
9.6%
i47
9.2%
d47
9.2%
P43
8.4%
_43
8.4%
025
 
4.9%
15
 
2.9%
Other values (26)76
14.8%
Distinct13
Distinct (%)17.1%
Missing2
Missing (%)2.6%
Memory size752.0 B
Period_07
17 
2
15 
Period_12
11 
3
10 
Period_08
Other values (8)
15 

Length

Max length64
Median length9
Mean length6.736842105
Min length1

Characters and Unicode

Total characters512
Distinct characters34
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)5.3%

Sample

1st rowPeriod_12
2nd rowPeriod_12
3rd rowPeriod_08
4th rowPeriod_07
5th rowPeriod_01

Common Values

ValueCountFrequency (%)
Period_0717
21.8%
215
19.2%
Period_1211
14.1%
310
12.8%
Period_088
10.3%
Period_133
 
3.8%
Period_113
 
3.8%
43
 
3.8%
12
 
2.6%
Period_011
 
1.3%
Other values (3)3
 
3.8%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:59.245623image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
period_0717
18.7%
215
16.5%
period_1211
12.1%
310
11.0%
period_088
8.8%
period_133
 
3.3%
period_113
 
3.3%
43
 
3.3%
at2
 
2.2%
12
 
2.2%
Other values (17)17
18.7%

Most occurring characters

ValueCountFrequency (%)
o51
10.0%
e51
10.0%
r48
9.4%
i47
9.2%
d46
9.0%
P43
 
8.4%
_43
 
8.4%
026
 
5.1%
226
 
5.1%
123
 
4.5%
Other values (24)108
21.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter289
56.4%
Decimal Number117
22.9%
Uppercase Letter45
 
8.8%
Connector Punctuation43
 
8.4%
Space Separator17
 
3.3%
Other Punctuation1
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o51
17.6%
e51
17.6%
r48
16.6%
i47
16.3%
d46
15.9%
t5
 
1.7%
s5
 
1.7%
a5
 
1.7%
n5
 
1.7%
m4
 
1.4%
Other values (10)22
7.6%
Decimal Number
ValueCountFrequency (%)
026
22.2%
226
22.2%
123
19.7%
717
14.5%
313
11.1%
88
 
6.8%
43
 
2.6%
51
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
P43
95.6%
I1
 
2.2%
D1
 
2.2%
Connector Punctuation
ValueCountFrequency (%)
_43
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin334
65.2%
Common178
34.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o51
15.3%
e51
15.3%
r48
14.4%
i47
14.1%
d46
13.8%
P43
12.9%
t5
 
1.5%
s5
 
1.5%
a5
 
1.5%
n5
 
1.5%
Other values (13)28
8.4%
Common
ValueCountFrequency (%)
_43
24.2%
026
14.6%
226
14.6%
123
12.9%
17
 
9.6%
717
 
9.6%
313
 
7.3%
88
 
4.5%
43
 
1.7%
?1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII512
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o51
10.0%
e51
10.0%
r48
9.4%
i47
9.2%
d46
9.0%
P43
 
8.4%
_43
 
8.4%
026
 
5.1%
226
 
5.1%
123
 
4.5%
Other values (24)108
21.1%
Distinct10
Distinct (%)13.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
LittleWindy
18 
Negligable
13 
Yes
12 
FirstFloor
No
Other values (5)
17 

Length

Max length102
Median length24
Mean length9.828947368
Min length2

Characters and Unicode

Total characters747
Distinct characters34
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st rowMaybe
2nd rowNo
3rd rowYes
4th rowYes
5th rowYes

Common Values

ValueCountFrequency (%)
LittleWindy18
23.1%
Negligable13
16.7%
Yes12
15.4%
FirstFloor9
11.5%
No7
 
9.0%
SecondFloor7
 
9.0%
GroundFloor6
 
7.7%
Maybe2
 
2.6%
On which floor is your work space located (work space is the place where you spend most of the time)1
 
1.3%
Air speed at this moment1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:59.380710image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:59.545055image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
littlewindy18
18.2%
negligable13
13.1%
yes12
12.1%
firstfloor9
9.1%
no7
 
7.1%
secondfloor7
 
7.1%
groundfloor6
 
6.1%
is2
 
2.0%
the2
 
2.0%
work2
 
2.0%
Other values (19)21
21.2%

Most occurring characters

ValueCountFrequency (%)
e78
 
10.4%
o74
 
9.9%
l69
 
9.2%
i64
 
8.6%
t53
 
7.1%
r43
 
5.8%
n34
 
4.6%
d34
 
4.6%
F31
 
4.1%
s29
 
3.9%
Other values (24)238
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter604
80.9%
Uppercase Letter116
 
15.5%
Space Separator25
 
3.3%
Open Punctuation1
 
0.1%
Close Punctuation1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e78
12.9%
o74
12.3%
l69
11.4%
i64
10.6%
t53
8.8%
r43
7.1%
n34
 
5.6%
d34
 
5.6%
s29
 
4.8%
g26
 
4.3%
Other values (11)100
16.6%
Uppercase Letter
ValueCountFrequency (%)
F31
26.7%
N20
17.2%
L18
15.5%
W18
15.5%
Y12
 
10.3%
S7
 
6.0%
G6
 
5.2%
M2
 
1.7%
O1
 
0.9%
A1
 
0.9%
Space Separator
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin720
96.4%
Common27
 
3.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e78
 
10.8%
o74
 
10.3%
l69
 
9.6%
i64
 
8.9%
t53
 
7.4%
r43
 
6.0%
n34
 
4.7%
d34
 
4.7%
F31
 
4.3%
s29
 
4.0%
Other values (21)211
29.3%
Common
ValueCountFrequency (%)
25
92.6%
(1
 
3.7%
)1
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII747
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e78
 
10.4%
o74
 
9.9%
l69
 
9.2%
i64
 
8.6%
t53
 
7.1%
r43
 
5.8%
n34
 
4.6%
d34
 
4.6%
F31
 
4.1%
s29
 
3.9%
Other values (24)238
31.9%
Distinct7
Distinct (%)9.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
3
31 
4
18 
2
11 
1
5
Other values (2)
 
2

Length

Max length71
Median length1
Mean length2.236842105
Min length1

Characters and Unicode

Total characters170
Distinct characters29
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st row3
2nd row3
3rd row3
4th row1
5th row1

Common Values

ValueCountFrequency (%)
331
39.7%
418
23.1%
211
 
14.1%
19
 
11.5%
55
 
6.4%
How accessible is from the parking lot to the main door of the college?1
 
1.3%
Ventilation and Air smell1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:06:59.719318image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:06:59.875424image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
331
33.7%
418
19.6%
211
 
12.0%
19
 
9.8%
55
 
5.4%
the3
 
3.3%
main1
 
1.1%
air1
 
1.1%
and1
 
1.1%
ventilation1
 
1.1%
Other values (11)11
 
12.0%

Most occurring characters

ValueCountFrequency (%)
331
18.2%
418
 
10.6%
16
 
9.4%
211
 
6.5%
o9
 
5.3%
e9
 
5.3%
19
 
5.3%
t7
 
4.1%
i7
 
4.1%
l7
 
4.1%
Other values (19)46
27.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter76
44.7%
Decimal Number74
43.5%
Space Separator16
 
9.4%
Uppercase Letter3
 
1.8%
Other Punctuation1
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o9
11.8%
e9
11.8%
t7
9.2%
i7
9.2%
l7
9.2%
a5
 
6.6%
n5
 
6.6%
s4
 
5.3%
r4
 
5.3%
c3
 
3.9%
Other values (9)16
21.1%
Decimal Number
ValueCountFrequency (%)
331
41.9%
418
24.3%
211
 
14.9%
19
 
12.2%
55
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
V1
33.3%
H1
33.3%
A1
33.3%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common91
53.5%
Latin79
46.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o9
11.4%
e9
11.4%
t7
 
8.9%
i7
 
8.9%
l7
 
8.9%
a5
 
6.3%
n5
 
6.3%
s4
 
5.1%
r4
 
5.1%
c3
 
3.8%
Other values (12)19
24.1%
Common
ValueCountFrequency (%)
331
34.1%
418
19.8%
16
17.6%
211
 
12.1%
19
 
9.9%
55
 
5.5%
?1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII170
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
331
18.2%
418
 
10.6%
16
 
9.4%
211
 
6.5%
o9
 
5.3%
e9
 
5.3%
19
 
5.3%
t7
 
4.1%
i7
 
4.1%
l7
 
4.1%
Other values (19)46
27.1%
Distinct10
Distinct (%)13.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
No
24 
3
16 
2
4
5
Other values (5)
15 

Length

Max length44
Median length1
Mean length2.592105263
Min length1

Characters and Unicode

Total characters197
Distinct characters30
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st row2
2nd row3
3rd row3
4th row1
5th row3

Common Values

ValueCountFrequency (%)
No24
30.8%
316
20.5%
27
 
9.0%
47
 
9.0%
57
 
9.0%
16
 
7.7%
Yes4
 
5.1%
Maybe3
 
3.8%
How is easy to go from one floor to another?1
 
1.3%
Do you smell odor or unusual smell?1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:07:00.022473image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:00.180657image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no24
26.4%
316
17.6%
27
 
7.7%
47
 
7.7%
57
 
7.7%
16
 
6.6%
yes4
 
4.4%
maybe3
 
3.3%
smell2
 
2.2%
to2
 
2.2%
Other values (13)13
14.3%

Most occurring characters

ValueCountFrequency (%)
o38
19.3%
N24
12.2%
316
 
8.1%
15
 
7.6%
e12
 
6.1%
s9
 
4.6%
27
 
3.6%
47
 
3.6%
57
 
3.6%
a6
 
3.0%
Other values (20)56
28.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter104
52.8%
Decimal Number43
21.8%
Uppercase Letter33
 
16.8%
Space Separator15
 
7.6%
Other Punctuation2
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o38
36.5%
e12
 
11.5%
s9
 
8.7%
a6
 
5.8%
l6
 
5.8%
r5
 
4.8%
y5
 
4.8%
u4
 
3.8%
b3
 
2.9%
t3
 
2.9%
Other values (8)13
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
N24
72.7%
Y4
 
12.1%
M3
 
9.1%
D1
 
3.0%
H1
 
3.0%
Decimal Number
ValueCountFrequency (%)
316
37.2%
27
16.3%
47
16.3%
57
16.3%
16
 
14.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Punctuation
ValueCountFrequency (%)
?2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin137
69.5%
Common60
30.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o38
27.7%
N24
17.5%
e12
 
8.8%
s9
 
6.6%
a6
 
4.4%
l6
 
4.4%
r5
 
3.6%
y5
 
3.6%
u4
 
2.9%
Y4
 
2.9%
Other values (13)24
17.5%
Common
ValueCountFrequency (%)
316
26.7%
15
25.0%
27
11.7%
47
11.7%
57
11.7%
16
 
10.0%
?2
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII197
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o38
19.3%
N24
12.2%
316
 
8.1%
15
 
7.6%
e12
 
6.1%
s9
 
4.6%
27
 
3.6%
47
 
3.6%
57
 
3.6%
a6
 
3.0%
Other values (20)56
28.4%

Do you feel comfortable under the current temperature ?
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct10
Distinct (%)13.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
No
27 
Yes
17 
2
Maybe
4
Other values (5)

Length

Max length57
Median length39
Mean length3.460526316
Min length1

Characters and Unicode

Total characters263
Distinct characters33
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)5.3%

Sample

1st rowMaybe
2nd rowNo
3rd rowMaybe
4th rowNo
5th rowMaybe

Common Values

ValueCountFrequency (%)
No27
34.6%
Yes17
21.8%
29
 
11.5%
Maybe8
 
10.3%
46
 
7.7%
35
 
6.4%
How easy is the horizontal circulation?1
 
1.3%
11
 
1.3%
51
 
1.3%
Do you feel sleepy or headache when you get to the room ?1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:07:00.340660image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:00.501252image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no27
29.0%
yes17
18.3%
29
 
9.7%
maybe8
 
8.6%
46
 
6.5%
35
 
5.4%
the2
 
2.2%
you2
 
2.2%
feel1
 
1.1%
room1
 
1.1%
Other values (15)15
16.1%

Most occurring characters

ValueCountFrequency (%)
o38
14.4%
e36
13.7%
N27
10.3%
s20
 
7.6%
17
 
6.5%
Y17
 
6.5%
a13
 
4.9%
y12
 
4.6%
29
 
3.4%
M8
 
3.0%
Other values (23)66
25.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter168
63.9%
Uppercase Letter54
 
20.5%
Decimal Number22
 
8.4%
Space Separator17
 
6.5%
Other Punctuation2
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o38
22.6%
e36
21.4%
s20
11.9%
a13
 
7.7%
y12
 
7.1%
b8
 
4.8%
h6
 
3.6%
t6
 
3.6%
i4
 
2.4%
r4
 
2.4%
Other values (11)21
12.5%
Uppercase Letter
ValueCountFrequency (%)
N27
50.0%
Y17
31.5%
M8
 
14.8%
H1
 
1.9%
D1
 
1.9%
Decimal Number
ValueCountFrequency (%)
29
40.9%
46
27.3%
35
22.7%
11
 
4.5%
51
 
4.5%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
?2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin222
84.4%
Common41
 
15.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o38
17.1%
e36
16.2%
N27
12.2%
s20
9.0%
Y17
7.7%
a13
 
5.9%
y12
 
5.4%
M8
 
3.6%
b8
 
3.6%
h6
 
2.7%
Other values (16)37
16.7%
Common
ValueCountFrequency (%)
17
41.5%
29
22.0%
46
 
14.6%
35
 
12.2%
?2
 
4.9%
11
 
2.4%
51
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII263
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o38
14.4%
e36
13.7%
N27
10.3%
s20
 
7.6%
17
 
6.5%
Y17
 
6.5%
a13
 
4.9%
y12
 
4.6%
29
 
3.4%
M8
 
3.0%
Other values (23)66
25.1%

How you describe the current temperature in this room?
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct7
Distinct (%)9.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
3
22 
4
19 
5
15 
2
12 
1
Other values (2)
 
2

Length

Max length62
Median length1
Mean length2.197368421
Min length1

Characters and Unicode

Total characters167
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st row2
2nd row3
3rd row2
4th row1
5th row3

Common Values

ValueCountFrequency (%)
322
28.2%
419
24.4%
515
19.2%
212
15.4%
16
 
7.7%
How easy is to get out of the building in emergency situation?1
 
1.3%
Comfortable under light colour 1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:07:00.661503image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:00.814117image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
322
24.4%
419
21.1%
515
16.7%
212
13.3%
16
 
6.7%
building1
 
1.1%
light1
 
1.1%
under1
 
1.1%
comfortable1
 
1.1%
situation1
 
1.1%
Other values (11)11
12.2%

Most occurring characters

ValueCountFrequency (%)
322
13.2%
419
11.4%
15
 
9.0%
515
 
9.0%
212
 
7.2%
o9
 
5.4%
e8
 
4.8%
t8
 
4.8%
i7
 
4.2%
16
 
3.6%
Other values (18)46
27.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter75
44.9%
Decimal Number74
44.3%
Space Separator15
 
9.0%
Uppercase Letter2
 
1.2%
Other Punctuation1
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o9
12.0%
e8
10.7%
t8
10.7%
i7
 
9.3%
u5
 
6.7%
n5
 
6.7%
l4
 
5.3%
g4
 
5.3%
r4
 
5.3%
s3
 
4.0%
Other values (9)18
24.0%
Decimal Number
ValueCountFrequency (%)
322
29.7%
419
25.7%
515
20.3%
212
16.2%
16
 
8.1%
Uppercase Letter
ValueCountFrequency (%)
H1
50.0%
C1
50.0%
Space Separator
ValueCountFrequency (%)
15
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common90
53.9%
Latin77
46.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o9
11.7%
e8
 
10.4%
t8
 
10.4%
i7
 
9.1%
u5
 
6.5%
n5
 
6.5%
l4
 
5.2%
g4
 
5.2%
r4
 
5.2%
s3
 
3.9%
Other values (11)20
26.0%
Common
ValueCountFrequency (%)
322
24.4%
419
21.1%
15
16.7%
515
16.7%
212
13.3%
16
 
6.7%
?1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII167
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
322
13.2%
419
11.4%
15
 
9.0%
515
 
9.0%
212
 
7.2%
o9
 
5.4%
e8
 
4.8%
t8
 
4.8%
i7
 
4.2%
16
 
3.6%
Other values (18)46
27.5%
Distinct10
Distinct (%)13.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
Yes
26 
No
12 
5
10 
4
10 
3
Other values (5)
10 

Length

Max length52
Median length37
Mean length3.25
Min length1

Characters and Unicode

Total characters247
Distinct characters33
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)3.9%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowYes
5th rowYes

Common Values

ValueCountFrequency (%)
Yes26
33.3%
No12
15.4%
510
 
12.8%
410
 
12.8%
38
 
10.3%
Maybe5
 
6.4%
22
 
2.6%
Do you know the route to the nearest emergency door?1
 
1.3%
Comfort under the current light level1
 
1.3%
11
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:07:00.962257image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:01.123598image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
yes26
28.9%
no12
13.3%
510
 
11.1%
410
 
11.1%
38
 
8.9%
maybe5
 
5.6%
the3
 
3.3%
22
 
2.2%
door1
 
1.1%
level1
 
1.1%
Other values (12)12
13.3%

Most occurring characters

ValueCountFrequency (%)
e44
17.8%
s27
10.9%
Y26
 
10.5%
o21
 
8.5%
14
 
5.7%
N12
 
4.9%
510
 
4.0%
410
 
4.0%
t9
 
3.6%
r8
 
3.2%
Other values (23)66
26.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter156
63.2%
Uppercase Letter45
 
18.2%
Decimal Number31
 
12.6%
Space Separator14
 
5.7%
Other Punctuation1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e44
28.2%
s27
17.3%
o21
13.5%
t9
 
5.8%
r8
 
5.1%
y7
 
4.5%
a6
 
3.8%
b5
 
3.2%
n5
 
3.2%
h4
 
2.6%
Other values (11)20
12.8%
Uppercase Letter
ValueCountFrequency (%)
Y26
57.8%
N12
26.7%
M5
 
11.1%
C1
 
2.2%
D1
 
2.2%
Decimal Number
ValueCountFrequency (%)
510
32.3%
410
32.3%
38
25.8%
22
 
6.5%
11
 
3.2%
Space Separator
ValueCountFrequency (%)
14
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin201
81.4%
Common46
 
18.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e44
21.9%
s27
13.4%
Y26
12.9%
o21
10.4%
N12
 
6.0%
t9
 
4.5%
r8
 
4.0%
y7
 
3.5%
a6
 
3.0%
b5
 
2.5%
Other values (16)36
17.9%
Common
ValueCountFrequency (%)
14
30.4%
510
21.7%
410
21.7%
38
17.4%
22
 
4.3%
?1
 
2.2%
11
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII247
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e44
17.8%
s27
10.9%
Y26
 
10.5%
o21
 
8.5%
14
 
5.7%
N12
 
4.9%
510
 
4.0%
410
 
4.0%
t9
 
3.6%
r8
 
3.2%
Other values (23)66
26.7%

Is there significant distraction from noise outside (in this moment) ?
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct10
Distinct (%)13.2%
Missing2
Missing (%)2.6%
Memory size752.0 B
No
28 
3
18 
Yes
10 
Maybe
5
Other values (5)
10 

Length

Max length99
Median length33
Mean length3.605263158
Min length1

Characters and Unicode

Total characters274
Distinct characters33
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st rowNo
2nd rowNo
3rd rowMaybe
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No28
35.9%
318
23.1%
Yes10
 
12.8%
Maybe5
 
6.4%
55
 
6.4%
44
 
5.1%
12
 
2.6%
22
 
2.6%
Does the temperature in this part of the building have a negative effect on your work performance? 1
 
1.3%
Describe the current light level 1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:07:01.284790image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:01.444421image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no28
29.2%
318
18.8%
yes10
 
10.4%
maybe5
 
5.2%
55
 
5.2%
44
 
4.2%
the3
 
3.1%
22
 
2.1%
12
 
2.1%
light1
 
1.0%
Other values (18)18
18.8%

Most occurring characters

ValueCountFrequency (%)
o34
12.4%
e34
12.4%
N28
 
10.2%
22
 
8.0%
318
 
6.6%
s13
 
4.7%
a11
 
4.0%
t11
 
4.0%
r10
 
3.6%
Y10
 
3.6%
Other values (23)83
30.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter175
63.9%
Uppercase Letter45
 
16.4%
Decimal Number31
 
11.3%
Space Separator22
 
8.0%
Other Punctuation1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o34
19.4%
e34
19.4%
s13
 
7.4%
a11
 
6.3%
t11
 
6.3%
r10
 
5.7%
i7
 
4.0%
b7
 
4.0%
n6
 
3.4%
h6
 
3.4%
Other values (12)36
20.6%
Decimal Number
ValueCountFrequency (%)
318
58.1%
55
 
16.1%
44
 
12.9%
12
 
6.5%
22
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
N28
62.2%
Y10
 
22.2%
M5
 
11.1%
D2
 
4.4%
Space Separator
ValueCountFrequency (%)
22
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin220
80.3%
Common54
 
19.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o34
15.5%
e34
15.5%
N28
12.7%
s13
 
5.9%
a11
 
5.0%
t11
 
5.0%
r10
 
4.5%
Y10
 
4.5%
i7
 
3.2%
b7
 
3.2%
Other values (16)55
25.0%
Common
ValueCountFrequency (%)
22
40.7%
318
33.3%
55
 
9.3%
44
 
7.4%
12
 
3.7%
22
 
3.7%
?1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII274
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o34
12.4%
e34
12.4%
N28
 
10.2%
22
 
8.0%
318
 
6.6%
s13
 
4.7%
a11
 
4.0%
t11
 
4.0%
r10
 
3.6%
Y10
 
3.6%
Other values (23)83
30.3%
Distinct11
Distinct (%)14.5%
Missing2
Missing (%)2.6%
Memory size752.0 B
yes
23 
No
21 
3
10 
1
Yes
Other values (6)
13 

Length

Max length82
Median length33
Mean length3.684210526
Min length1

Characters and Unicode

Total characters280
Distinct characters35
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)3.9%

Sample

1st rowYes
2nd rowMaybe
3rd rowMaybe
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
yes23
29.5%
No21
26.9%
310
12.8%
15
 
6.4%
Yes4
 
5.1%
Maybe4
 
5.1%
24
 
5.1%
42
 
2.6%
How would you describe the summer indoor air temperature (your most time feeling)?1
 
1.3%
51
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:07:01.791776image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
yes27
29.3%
no21
22.8%
310
 
10.9%
15
 
5.4%
maybe4
 
4.3%
24
 
4.3%
42
 
2.2%
your1
 
1.1%
light1
 
1.1%
natural1
 
1.1%
Other values (16)16
17.4%

Most occurring characters

ValueCountFrequency (%)
e41
14.6%
y30
 
10.7%
s30
 
10.7%
o30
 
10.7%
N21
 
7.5%
16
 
5.7%
310
 
3.6%
a10
 
3.6%
i9
 
3.2%
t8
 
2.9%
Other values (25)75
26.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter208
74.3%
Uppercase Letter31
 
11.1%
Decimal Number22
 
7.9%
Space Separator16
 
5.7%
Close Punctuation1
 
0.4%
Other Punctuation1
 
0.4%
Open Punctuation1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e41
19.7%
y30
14.4%
s30
14.4%
o30
14.4%
a10
 
4.8%
i9
 
4.3%
t8
 
3.8%
r8
 
3.8%
u6
 
2.9%
l6
 
2.9%
Other values (11)30
14.4%
Uppercase Letter
ValueCountFrequency (%)
N21
67.7%
M4
 
12.9%
Y4
 
12.9%
A1
 
3.2%
H1
 
3.2%
Decimal Number
ValueCountFrequency (%)
310
45.5%
15
22.7%
24
 
18.2%
42
 
9.1%
51
 
4.5%
Space Separator
ValueCountFrequency (%)
16
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin239
85.4%
Common41
 
14.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e41
17.2%
y30
12.6%
s30
12.6%
o30
12.6%
N21
8.8%
a10
 
4.2%
i9
 
3.8%
t8
 
3.3%
r8
 
3.3%
u6
 
2.5%
Other values (16)46
19.2%
Common
ValueCountFrequency (%)
16
39.0%
310
24.4%
15
 
12.2%
24
 
9.8%
42
 
4.9%
)1
 
2.4%
51
 
2.4%
?1
 
2.4%
(1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII280
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e41
14.6%
y30
 
10.7%
s30
 
10.7%
o30
 
10.7%
N21
 
7.5%
16
 
5.7%
310
 
3.6%
a10
 
3.6%
i9
 
3.2%
t8
 
2.9%
Other values (25)75
26.8%

How would you describe the noise in building generally "most time feeling"?
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct8
Distinct (%)10.5%
Missing2
Missing (%)2.6%
Memory size752.0 B
No
25 
3
23 
4
11 
2
Yes
Other values (3)

Length

Max length82
Median length1
Mean length3.118421053
Min length1

Characters and Unicode

Total characters237
Distinct characters34
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)3.9%

Sample

1st row3
2nd row3
3rd row3
4th row4
5th row2

Common Values

ValueCountFrequency (%)
No25
32.1%
323
29.5%
411
14.1%
28
 
10.3%
Yes6
 
7.7%
How would you describe the winter indoor air temperature (your most time feeling)?1
 
1.3%
11
 
1.3%
Is there any luminare is OFF at this moment?1
 
1.3%
(Missing)2
 
2.6%

Length

2022-08-24T15:07:01.937044image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:02.100324image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no25
26.0%
323
24.0%
411
11.5%
28
 
8.3%
yes6
 
6.2%
is2
 
2.1%
time1
 
1.0%
this1
 
1.0%
at1
 
1.0%
off1
 
1.0%
Other values (17)17
17.7%

Most occurring characters

ValueCountFrequency (%)
o33
13.9%
N25
 
10.5%
323
 
9.7%
20
 
8.4%
e20
 
8.4%
411
 
4.6%
s11
 
4.6%
t10
 
4.2%
r9
 
3.8%
i9
 
3.8%
Other values (24)66
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter134
56.5%
Decimal Number43
 
18.1%
Uppercase Letter36
 
15.2%
Space Separator20
 
8.4%
Other Punctuation2
 
0.8%
Open Punctuation1
 
0.4%
Close Punctuation1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o33
24.6%
e20
14.9%
s11
 
8.2%
t10
 
7.5%
r9
 
6.7%
i9
 
6.7%
m6
 
4.5%
n6
 
4.5%
a5
 
3.7%
u5
 
3.7%
Other values (10)20
14.9%
Uppercase Letter
ValueCountFrequency (%)
N25
69.4%
Y6
 
16.7%
F2
 
5.6%
H1
 
2.8%
I1
 
2.8%
O1
 
2.8%
Decimal Number
ValueCountFrequency (%)
323
53.5%
411
25.6%
28
 
18.6%
11
 
2.3%
Space Separator
ValueCountFrequency (%)
20
100.0%
Other Punctuation
ValueCountFrequency (%)
?2
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin170
71.7%
Common67
 
28.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o33
19.4%
N25
14.7%
e20
11.8%
s11
 
6.5%
t10
 
5.9%
r9
 
5.3%
i9
 
5.3%
Y6
 
3.5%
m6
 
3.5%
n6
 
3.5%
Other values (16)35
20.6%
Common
ValueCountFrequency (%)
323
34.3%
20
29.9%
411
16.4%
28
 
11.9%
?2
 
3.0%
(1
 
1.5%
)1
 
1.5%
11
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII237
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o33
13.9%
N25
 
10.5%
323
 
9.7%
20
 
8.4%
e20
 
8.4%
411
 
4.6%
s11
 
4.6%
t10
 
4.2%
r9
 
3.8%
i9
 
3.8%
Other values (24)66
27.8%

How would describe noise at this moment?
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct8
Distinct (%)18.2%
Missing34
Missing (%)43.6%
Memory size752.0 B
No
13 
3
4
Yes
2
Other values (3)

Length

Max length55
Median length5
Mean length3.068181818
Min length1

Characters and Unicode

Total characters135
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.5%

Sample

1st row4
2nd row3
3rd row3
4th row3
5th row2

Common Values

ValueCountFrequency (%)
No13
 
16.7%
39
 
11.5%
48
 
10.3%
Yes6
 
7.7%
23
 
3.8%
Maybe3
 
3.8%
51
 
1.3%
Do you feel comfortable under the current temperature? 1
 
1.3%
(Missing)34
43.6%

Length

2022-08-24T15:07:02.250984image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:02.403201image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no13
25.5%
39
17.6%
48
15.7%
yes6
11.8%
23
 
5.9%
maybe3
 
5.9%
51
 
2.0%
do1
 
2.0%
you1
 
2.0%
feel1
 
2.0%
Other values (5)5
 
9.8%

Most occurring characters

ValueCountFrequency (%)
e18
13.3%
o17
12.6%
N13
 
9.6%
39
 
6.7%
48
 
5.9%
8
 
5.9%
Y6
 
4.4%
s6
 
4.4%
r6
 
4.4%
t5
 
3.7%
Other values (17)39
28.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter82
60.7%
Uppercase Letter23
 
17.0%
Decimal Number21
 
15.6%
Space Separator8
 
5.9%
Other Punctuation1
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e18
22.0%
o17
20.7%
s6
 
7.3%
r6
 
7.3%
t5
 
6.1%
a5
 
6.1%
u4
 
4.9%
b4
 
4.9%
y4
 
4.9%
f2
 
2.4%
Other values (7)11
13.4%
Uppercase Letter
ValueCountFrequency (%)
N13
56.5%
Y6
26.1%
M3
 
13.0%
D1
 
4.3%
Decimal Number
ValueCountFrequency (%)
39
42.9%
48
38.1%
23
 
14.3%
51
 
4.8%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin105
77.8%
Common30
 
22.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e18
17.1%
o17
16.2%
N13
12.4%
Y6
 
5.7%
s6
 
5.7%
r6
 
5.7%
t5
 
4.8%
a5
 
4.8%
u4
 
3.8%
b4
 
3.8%
Other values (11)21
20.0%
Common
ValueCountFrequency (%)
39
30.0%
48
26.7%
8
26.7%
23
 
10.0%
51
 
3.3%
?1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e18
13.3%
o17
12.6%
N13
 
9.6%
39
 
6.7%
48
 
5.9%
8
 
5.9%
Y6
 
4.4%
s6
 
4.4%
r6
 
4.4%
t5
 
3.7%
Other values (17)39
28.9%
Distinct8
Distinct (%)18.2%
Missing34
Missing (%)43.6%
Memory size752.0 B
No
14 
2
Yes
3
4
Other values (3)

Length

Max length54
Median length28.5
Mean length2.840909091
Min length1

Characters and Unicode

Total characters125
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowYes

Common Values

ValueCountFrequency (%)
No14
17.9%
29
 
11.5%
Yes7
 
9.0%
36
 
7.7%
43
 
3.8%
52
 
2.6%
12
 
2.6%
How you describe the current temperature in this room?1
 
1.3%
(Missing)34
43.6%

Length

2022-08-24T15:07:02.549089image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:02.702072image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no14
26.9%
29
17.3%
yes7
13.5%
36
11.5%
43
 
5.8%
52
 
3.8%
12
 
3.8%
how1
 
1.9%
you1
 
1.9%
describe1
 
1.9%
Other values (6)6
11.5%

Most occurring characters

ValueCountFrequency (%)
o18
14.4%
N14
11.2%
e14
11.2%
29
 
7.2%
s9
 
7.2%
8
 
6.4%
Y7
 
5.6%
36
 
4.8%
r6
 
4.8%
t5
 
4.0%
Other values (17)29
23.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter72
57.6%
Uppercase Letter22
 
17.6%
Decimal Number22
 
17.6%
Space Separator8
 
6.4%
Other Punctuation1
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o18
25.0%
e14
19.4%
s9
12.5%
r6
 
8.3%
t5
 
6.9%
u3
 
4.2%
i3
 
4.2%
h2
 
2.8%
m2
 
2.8%
c2
 
2.8%
Other values (7)8
11.1%
Decimal Number
ValueCountFrequency (%)
29
40.9%
36
27.3%
43
 
13.6%
12
 
9.1%
52
 
9.1%
Uppercase Letter
ValueCountFrequency (%)
N14
63.6%
Y7
31.8%
H1
 
4.5%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin94
75.2%
Common31
 
24.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o18
19.1%
N14
14.9%
e14
14.9%
s9
9.6%
Y7
 
7.4%
r6
 
6.4%
t5
 
5.3%
u3
 
3.2%
i3
 
3.2%
h2
 
2.1%
Other values (10)13
13.8%
Common
ValueCountFrequency (%)
29
29.0%
8
25.8%
36
19.4%
43
 
9.7%
12
 
6.5%
52
 
6.5%
?1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII125
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o18
14.4%
N14
11.2%
e14
11.2%
29
 
7.2%
s9
 
7.2%
8
 
6.4%
Y7
 
5.6%
36
 
4.8%
r6
 
4.8%
t5
 
4.0%
Other values (17)29
23.2%

Do you have control over air condition system ?
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)9.1%
Missing34
Missing (%)43.6%
Memory size752.0 B
No
32 
Maybe
Yes
Does the distraction from noise in this part of building have a negative effect on your work performance (most time feeling)?
 
1

Length

Max length125
Median length2
Mean length5.318181818
Min length2

Characters and Unicode

Total characters234
Distinct characters30
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st rowNo
2nd rowYes
3rd rowNo
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No32
41.0%
Maybe6
 
7.7%
Yes5
 
6.4%
Does the distraction from noise in this part of building have a negative effect on your work performance (most time feeling)?1
 
1.3%
(Missing)34
43.6%

Length

2022-08-24T15:07:02.849210image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:02.992370image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no32
50.0%
maybe6
 
9.4%
yes5
 
7.8%
have1
 
1.6%
time1
 
1.6%
most1
 
1.6%
performance1
 
1.6%
work1
 
1.6%
your1
 
1.6%
on1
 
1.6%
Other values (14)14
21.9%

Most occurring characters

ValueCountFrequency (%)
o42
17.9%
N32
13.7%
e24
 
10.3%
20
 
8.5%
a12
 
5.1%
i10
 
4.3%
s10
 
4.3%
t9
 
3.8%
n8
 
3.4%
r7
 
3.0%
Other values (20)60
25.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter167
71.4%
Uppercase Letter44
 
18.8%
Space Separator20
 
8.5%
Open Punctuation1
 
0.4%
Close Punctuation1
 
0.4%
Other Punctuation1
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o42
25.1%
e24
14.4%
a12
 
7.2%
i10
 
6.0%
s10
 
6.0%
t9
 
5.4%
n8
 
4.8%
r7
 
4.2%
b7
 
4.2%
y7
 
4.2%
Other values (12)31
18.6%
Uppercase Letter
ValueCountFrequency (%)
N32
72.7%
M6
 
13.6%
Y5
 
11.4%
D1
 
2.3%
Space Separator
ValueCountFrequency (%)
20
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin211
90.2%
Common23
 
9.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o42
19.9%
N32
15.2%
e24
11.4%
a12
 
5.7%
i10
 
4.7%
s10
 
4.7%
t9
 
4.3%
n8
 
3.8%
r7
 
3.3%
b7
 
3.3%
Other values (16)50
23.7%
Common
ValueCountFrequency (%)
20
87.0%
(1
 
4.3%
)1
 
4.3%
?1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o42
17.9%
N32
13.7%
e24
 
10.3%
20
 
8.5%
a12
 
5.1%
i10
 
4.3%
s10
 
4.3%
t9
 
3.8%
n8
 
3.4%
r7
 
3.0%
Other values (20)60
25.6%
Distinct9
Distinct (%)20.5%
Missing34
Missing (%)43.6%
Memory size752.0 B
No
15 
2
3
4
Yes
Other values (4)

Length

Max length70
Median length5
Mean length3.318181818
Min length1

Characters and Unicode

Total characters146
Distinct characters30
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.5%

Sample

1st row3
2nd row4
3rd row4
4th row3
5th row2

Common Values

ValueCountFrequency (%)
No15
19.2%
28
 
10.3%
35
 
6.4%
45
 
6.4%
Yes5
 
6.4%
12
 
2.6%
Maybe2
 
2.6%
51
 
1.3%
Is there significant distraction from noise outside (at this moment)? 1
 
1.3%
(Missing)34
43.6%

Length

2022-08-24T15:07:03.131716image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:03.296059image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no15
28.3%
28
15.1%
35
 
9.4%
45
 
9.4%
yes5
 
9.4%
12
 
3.8%
maybe2
 
3.8%
from1
 
1.9%
this1
 
1.9%
at1
 
1.9%
Other values (8)8
15.1%

Most occurring characters

ValueCountFrequency (%)
o20
13.7%
N15
 
10.3%
e12
 
8.2%
s11
 
7.5%
10
 
6.8%
i8
 
5.5%
28
 
5.5%
t8
 
5.5%
Y5
 
3.4%
35
 
3.4%
Other values (20)44
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter89
61.0%
Uppercase Letter23
 
15.8%
Decimal Number21
 
14.4%
Space Separator10
 
6.8%
Open Punctuation1
 
0.7%
Close Punctuation1
 
0.7%
Other Punctuation1
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o20
22.5%
e12
13.5%
s11
12.4%
i8
 
9.0%
t8
 
9.0%
a5
 
5.6%
n5
 
5.6%
r3
 
3.4%
m3
 
3.4%
d2
 
2.2%
Other values (7)12
13.5%
Decimal Number
ValueCountFrequency (%)
28
38.1%
35
23.8%
45
23.8%
12
 
9.5%
51
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
N15
65.2%
Y5
 
21.7%
M2
 
8.7%
I1
 
4.3%
Space Separator
ValueCountFrequency (%)
10
100.0%
Open Punctuation
ValueCountFrequency (%)
(1
100.0%
Close Punctuation
ValueCountFrequency (%)
)1
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin112
76.7%
Common34
 
23.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o20
17.9%
N15
13.4%
e12
10.7%
s11
9.8%
i8
 
7.1%
t8
 
7.1%
Y5
 
4.5%
a5
 
4.5%
n5
 
4.5%
r3
 
2.7%
Other values (11)20
17.9%
Common
ValueCountFrequency (%)
10
29.4%
28
23.5%
35
14.7%
45
14.7%
12
 
5.9%
51
 
2.9%
(1
 
2.9%
)1
 
2.9%
?1
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII146
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o20
13.7%
N15
 
10.3%
e12
 
8.2%
s11
 
7.5%
10
 
6.8%
i8
 
5.5%
28
 
5.5%
t8
 
5.5%
Y5
 
3.4%
35
 
3.4%
Other values (20)44
30.1%

Do you smell odor or unusual smell in your work-space "most time feeling"?
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)9.1%
Missing34
Missing (%)43.6%
Memory size752.0 B
No
28 
Yes
13 
Maybe
 
2
Is there significant distraction from background noise (machine and undefined noise sources) (at this moment)?
 
1

Length

Max length111
Median length2
Mean length4.909090909
Min length2

Characters and Unicode

Total characters216
Distinct characters26
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st rowMaybe
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No28
35.9%
Yes13
 
16.7%
Maybe2
 
2.6%
Is there significant distraction from background noise (machine and undefined noise sources) (at this moment)? 1
 
1.3%
(Missing)34
43.6%

Length

2022-08-24T15:07:03.447372image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:03.585719image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no28
48.3%
yes13
22.4%
maybe2
 
3.4%
noise2
 
3.4%
machine1
 
1.7%
this1
 
1.7%
at1
 
1.7%
sources1
 
1.7%
undefined1
 
1.7%
and1
 
1.7%
Other values (7)7
 
12.1%

Most occurring characters

ValueCountFrequency (%)
o35
16.2%
N28
13.0%
e24
11.1%
s21
9.7%
15
 
6.9%
Y13
 
6.0%
n11
 
5.1%
i10
 
4.6%
a8
 
3.7%
t7
 
3.2%
Other values (16)44
20.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter152
70.4%
Uppercase Letter44
 
20.4%
Space Separator15
 
6.9%
Open Punctuation2
 
0.9%
Close Punctuation2
 
0.9%
Other Punctuation1
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o35
23.0%
e24
15.8%
s21
13.8%
n11
 
7.2%
i10
 
6.6%
a8
 
5.3%
t7
 
4.6%
d5
 
3.3%
c5
 
3.3%
r5
 
3.3%
Other values (8)21
13.8%
Uppercase Letter
ValueCountFrequency (%)
N28
63.6%
Y13
29.5%
M2
 
4.5%
I1
 
2.3%
Space Separator
ValueCountFrequency (%)
15
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin196
90.7%
Common20
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o35
17.9%
N28
14.3%
e24
12.2%
s21
10.7%
Y13
 
6.6%
n11
 
5.6%
i10
 
5.1%
a8
 
4.1%
t7
 
3.6%
d5
 
2.6%
Other values (12)34
17.3%
Common
ValueCountFrequency (%)
15
75.0%
(2
 
10.0%
)2
 
10.0%
?1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o35
16.2%
N28
13.0%
e24
11.1%
s21
9.7%
15
 
6.9%
Y13
 
6.0%
n11
 
5.1%
i10
 
4.6%
a8
 
3.7%
t7
 
3.2%
Other values (16)44
20.4%
Distinct8
Distinct (%)18.2%
Missing34
Missing (%)43.6%
Memory size752.0 B
No
13 
3
5
2
4
Other values (3)

Length

Max length55
Median length30
Mean length3.068181818
Min length1

Characters and Unicode

Total characters135
Distinct characters27
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st rowNo
2nd rowNo
3rd rowYes
4th rowNo
5th rowYes

Common Values

ValueCountFrequency (%)
No13
 
16.7%
37
 
9.0%
55
 
6.4%
25
 
6.4%
45
 
6.4%
Yes4
 
5.1%
Maybe4
 
5.1%
How would you describe the noise in building generally?1
 
1.3%
(Missing)34
43.6%

Length

2022-08-24T15:07:03.717620image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:03.872534image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no13
25.0%
37
13.5%
55
 
9.6%
25
 
9.6%
45
 
9.6%
yes4
 
7.7%
maybe4
 
7.7%
how1
 
1.9%
would1
 
1.9%
you1
 
1.9%
Other values (6)6
11.5%

Most occurring characters

ValueCountFrequency (%)
o17
 
12.6%
e14
 
10.4%
N13
 
9.6%
8
 
5.9%
37
 
5.2%
b6
 
4.4%
s6
 
4.4%
y6
 
4.4%
a5
 
3.7%
45
 
3.7%
Other values (17)48
35.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter82
60.7%
Uppercase Letter22
 
16.3%
Decimal Number22
 
16.3%
Space Separator8
 
5.9%
Other Punctuation1
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o17
20.7%
e14
17.1%
b6
 
7.3%
s6
 
7.3%
y6
 
7.3%
a5
 
6.1%
i5
 
6.1%
l4
 
4.9%
n4
 
4.9%
u3
 
3.7%
Other values (7)12
14.6%
Uppercase Letter
ValueCountFrequency (%)
N13
59.1%
Y4
 
18.2%
M4
 
18.2%
H1
 
4.5%
Decimal Number
ValueCountFrequency (%)
37
31.8%
45
22.7%
25
22.7%
55
22.7%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin104
77.0%
Common31
 
23.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o17
16.3%
e14
13.5%
N13
12.5%
b6
 
5.8%
s6
 
5.8%
y6
 
5.8%
a5
 
4.8%
i5
 
4.8%
Y4
 
3.8%
M4
 
3.8%
Other values (11)24
23.1%
Common
ValueCountFrequency (%)
8
25.8%
37
22.6%
45
16.1%
25
16.1%
55
16.1%
?1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o17
 
12.6%
e14
 
10.4%
N13
 
9.6%
8
 
5.9%
37
 
5.2%
b6
 
4.4%
s6
 
4.4%
y6
 
4.4%
a5
 
3.7%
45
 
3.7%
Other values (17)48
35.6%

Right now, do you smell unusual smell?
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct9
Distinct (%)20.5%
Missing34
Missing (%)43.6%
Memory size752.0 B
no
17 
4
5
3
2
Other values (4)

Length

Max length41
Median length23
Mean length2.568181818
Min length1

Characters and Unicode

Total characters113
Distinct characters25
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.5%

Sample

1st rowno
2nd rowmaybe
3rd rowno
4th rowno
5th rowyes

Common Values

ValueCountFrequency (%)
no17
21.8%
49
 
11.5%
55
 
6.4%
34
 
5.1%
23
 
3.8%
maybe2
 
2.6%
yes2
 
2.6%
How would describe noise at this moment? 1
 
1.3%
11
 
1.3%
(Missing)34
43.6%

Length

2022-08-24T15:07:04.030373image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:04.194659image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no17
34.0%
49
18.0%
55
 
10.0%
34
 
8.0%
23
 
6.0%
maybe2
 
4.0%
yes2
 
4.0%
how1
 
2.0%
would1
 
2.0%
describe1
 
2.0%
Other values (5)5
 
10.0%

Most occurring characters

ValueCountFrequency (%)
o21
18.6%
n19
16.8%
49
 
8.0%
e8
 
7.1%
7
 
6.2%
55
 
4.4%
s5
 
4.4%
34
 
3.5%
m4
 
3.5%
y4
 
3.5%
Other values (15)27
23.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter82
72.6%
Decimal Number22
 
19.5%
Space Separator7
 
6.2%
Other Punctuation1
 
0.9%
Uppercase Letter1
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o21
25.6%
n19
23.2%
e8
 
9.8%
s5
 
6.1%
m4
 
4.9%
y4
 
4.9%
b3
 
3.7%
i3
 
3.7%
a3
 
3.7%
t3
 
3.7%
Other values (7)9
11.0%
Decimal Number
ValueCountFrequency (%)
49
40.9%
55
22.7%
34
18.2%
23
 
13.6%
11
 
4.5%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%
Uppercase Letter
ValueCountFrequency (%)
H1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin83
73.5%
Common30
 
26.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o21
25.3%
n19
22.9%
e8
 
9.6%
s5
 
6.0%
m4
 
4.8%
y4
 
4.8%
b3
 
3.6%
i3
 
3.6%
a3
 
3.6%
t3
 
3.6%
Other values (8)10
12.0%
Common
ValueCountFrequency (%)
49
30.0%
7
23.3%
55
16.7%
34
13.3%
23
 
10.0%
?1
 
3.3%
11
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII113
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o21
18.6%
n19
16.8%
49
 
8.0%
e8
 
7.1%
7
 
6.2%
55
 
4.4%
s5
 
4.4%
34
 
3.5%
m4
 
3.5%
y4
 
3.5%
Other values (15)27
23.9%
Distinct9
Distinct (%)20.5%
Missing34
Missing (%)43.6%
Memory size752.0 B
1
11 
Yes
10 
No
2
Maybe
Other values (4)

Length

Max length60
Median length32.5
Mean length3.25
Min length1

Characters and Unicode

Total characters143
Distinct characters30
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.5%

Sample

1st rowNo
2nd rowYes
3rd rowMaybe
4th rowYes
5th rowNo

Common Values

ValueCountFrequency (%)
111
 
14.1%
Yes10
 
12.8%
No8
 
10.3%
25
 
6.4%
Maybe3
 
3.8%
33
 
3.8%
42
 
2.6%
How would you rate the level of cleanliness of the building?1
 
1.3%
51
 
1.3%
(Missing)34
43.6%

Length

2022-08-24T15:07:04.346331image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:04.505077image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
111
20.4%
yes10
18.5%
no8
14.8%
25
9.3%
maybe3
 
5.6%
33
 
5.6%
42
 
3.7%
of2
 
3.7%
the2
 
3.7%
level1
 
1.9%
Other values (7)7
13.0%

Most occurring characters

ValueCountFrequency (%)
e20
14.0%
o13
 
9.1%
s12
 
8.4%
111
 
7.7%
Y10
 
7.0%
10
 
7.0%
N8
 
5.6%
l6
 
4.2%
25
 
3.5%
a5
 
3.5%
Other values (20)43
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter88
61.5%
Decimal Number22
 
15.4%
Uppercase Letter22
 
15.4%
Space Separator10
 
7.0%
Other Punctuation1
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e20
22.7%
o13
14.8%
s12
13.6%
l6
 
6.8%
a5
 
5.7%
y4
 
4.5%
b4
 
4.5%
t3
 
3.4%
i3
 
3.4%
n3
 
3.4%
Other values (9)15
17.0%
Decimal Number
ValueCountFrequency (%)
111
50.0%
25
22.7%
33
 
13.6%
42
 
9.1%
51
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
Y10
45.5%
N8
36.4%
M3
 
13.6%
H1
 
4.5%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin110
76.9%
Common33
 
23.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e20
18.2%
o13
11.8%
s12
10.9%
Y10
 
9.1%
N8
 
7.3%
l6
 
5.5%
a5
 
4.5%
y4
 
3.6%
b4
 
3.6%
t3
 
2.7%
Other values (13)25
22.7%
Common
ValueCountFrequency (%)
111
33.3%
10
30.3%
25
15.2%
33
 
9.1%
42
 
6.1%
?1
 
3.0%
51
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII143
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e20
14.0%
o13
 
9.1%
s12
 
8.4%
111
 
7.7%
Y10
 
7.0%
10
 
7.0%
N8
 
5.6%
l6
 
4.2%
25
 
3.5%
a5
 
3.5%
Other values (20)43
30.1%

Is there availability of natural light?
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6
Distinct (%)13.6%
Missing34
Missing (%)43.6%
Memory size752.0 B
1
17 
3
12 
2
4
5

Length

Max length29
Median length1
Mean length1.636363636
Min length1

Characters and Unicode

Total characters72
Distinct characters23
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row4
2nd row3
3rd row2
4th row3
5th row1

Common Values

ValueCountFrequency (%)
117
21.8%
312
 
15.4%
27
 
9.0%
45
 
6.4%
52
 
2.6%
How clean is your work-space?1
 
1.3%
(Missing)34
43.6%

Length

2022-08-24T15:07:04.655056image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:04.802395image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
117
35.4%
312
25.0%
27
14.6%
45
 
10.4%
52
 
4.2%
how1
 
2.1%
clean1
 
2.1%
is1
 
2.1%
your1
 
2.1%
work-space1
 
2.1%

Most occurring characters

ValueCountFrequency (%)
117
23.6%
312
16.7%
27
9.7%
45
 
6.9%
4
 
5.6%
o3
 
4.2%
r2
 
2.8%
s2
 
2.8%
a2
 
2.8%
e2
 
2.8%
Other values (13)16
22.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number43
59.7%
Lowercase Letter22
30.6%
Space Separator4
 
5.6%
Uppercase Letter1
 
1.4%
Dash Punctuation1
 
1.4%
Other Punctuation1
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3
13.6%
r2
9.1%
s2
9.1%
a2
9.1%
e2
9.1%
c2
9.1%
w2
9.1%
l1
 
4.5%
n1
 
4.5%
i1
 
4.5%
Other values (4)4
18.2%
Decimal Number
ValueCountFrequency (%)
117
39.5%
312
27.9%
27
16.3%
45
 
11.6%
52
 
4.7%
Space Separator
ValueCountFrequency (%)
4
100.0%
Uppercase Letter
ValueCountFrequency (%)
H1
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common49
68.1%
Latin23
31.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o3
13.0%
r2
 
8.7%
s2
 
8.7%
a2
 
8.7%
e2
 
8.7%
c2
 
8.7%
w2
 
8.7%
l1
 
4.3%
n1
 
4.3%
i1
 
4.3%
Other values (5)5
21.7%
Common
ValueCountFrequency (%)
117
34.7%
312
24.5%
27
14.3%
45
 
10.2%
4
 
8.2%
52
 
4.1%
-1
 
2.0%
?1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII72
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
23.6%
312
16.7%
27
9.7%
45
 
6.9%
4
 
5.6%
o3
 
4.2%
r2
 
2.8%
s2
 
2.8%
a2
 
2.8%
e2
 
2.8%
Other values (13)16
22.2%

Are there blinds or shutters blocking the natural light ?
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)9.1%
Missing34
Missing (%)43.6%
Memory size752.0 B
Yes
21 
No
16 
Maybe
Does the quality of air in this part of building have a negative effect on your work performance?
 
1

Length

Max length97
Median length5
Mean length5.045454545
Min length2

Characters and Unicode

Total characters222
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowYes
5th rowYes

Common Values

ValueCountFrequency (%)
Yes21
26.9%
No16
20.5%
Maybe6
 
7.7%
Does the quality of air in this part of building have a negative effect on your work performance?1
 
1.3%
(Missing)34
43.6%

Length

2022-08-24T15:07:04.936199image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:05.074776image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
yes21
34.4%
no16
26.2%
maybe6
 
9.8%
of2
 
3.3%
have1
 
1.6%
work1
 
1.6%
your1
 
1.6%
on1
 
1.6%
effect1
 
1.6%
negative1
 
1.6%
Other values (10)10
16.4%

Most occurring characters

ValueCountFrequency (%)
e36
16.2%
s23
10.4%
o23
10.4%
Y21
9.5%
17
 
7.7%
N16
 
7.2%
a13
 
5.9%
y8
 
3.6%
i7
 
3.2%
b7
 
3.2%
Other values (19)51
23.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter160
72.1%
Uppercase Letter44
 
19.8%
Space Separator17
 
7.7%
Other Punctuation1
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e36
22.5%
s23
14.4%
o23
14.4%
a13
 
8.1%
y8
 
5.0%
i7
 
4.4%
b7
 
4.4%
t6
 
3.8%
r6
 
3.8%
n5
 
3.1%
Other values (13)26
16.2%
Uppercase Letter
ValueCountFrequency (%)
Y21
47.7%
N16
36.4%
M6
 
13.6%
D1
 
2.3%
Space Separator
ValueCountFrequency (%)
17
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin204
91.9%
Common18
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e36
17.6%
s23
11.3%
o23
11.3%
Y21
10.3%
N16
 
7.8%
a13
 
6.4%
y8
 
3.9%
i7
 
3.4%
b7
 
3.4%
M6
 
2.9%
Other values (17)44
21.6%
Common
ValueCountFrequency (%)
17
94.4%
?1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII222
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e36
16.2%
s23
10.4%
o23
10.4%
Y21
9.5%
17
 
7.7%
N16
 
7.2%
a13
 
5.9%
y8
 
3.6%
i7
 
3.2%
b7
 
3.2%
Other values (19)51
23.0%

Do you have control over artificial lightning ?
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)9.1%
Missing34
Missing (%)43.6%
Memory size752.0 B
Yes
27 
No
11 
Maybe
Do you have control over air condition system?
 
1

Length

Max length46
Median length3
Mean length3.954545455
Min length2

Characters and Unicode

Total characters174
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st rowYes
2nd rowNo
3rd rowYes
4th rowYes
5th rowNo

Common Values

ValueCountFrequency (%)
Yes27
34.6%
No11
 
14.1%
Maybe5
 
6.4%
Do you have control over air condition system?1
 
1.3%
(Missing)34
43.6%

Length

2022-08-24T15:07:05.204007image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:05.339330image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
yes27
52.9%
no11
21.6%
maybe5
 
9.8%
do1
 
2.0%
you1
 
2.0%
have1
 
2.0%
control1
 
2.0%
over1
 
2.0%
air1
 
2.0%
condition1
 
2.0%

Most occurring characters

ValueCountFrequency (%)
e35
20.1%
s29
16.7%
Y27
15.5%
o18
10.3%
N11
 
6.3%
a7
 
4.0%
y7
 
4.0%
7
 
4.0%
M5
 
2.9%
b5
 
2.9%
Other values (13)23
13.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter122
70.1%
Uppercase Letter44
 
25.3%
Space Separator7
 
4.0%
Other Punctuation1
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e35
28.7%
s29
23.8%
o18
14.8%
a7
 
5.7%
y7
 
5.7%
b5
 
4.1%
n3
 
2.5%
t3
 
2.5%
r3
 
2.5%
i3
 
2.5%
Other values (7)9
 
7.4%
Uppercase Letter
ValueCountFrequency (%)
Y27
61.4%
N11
25.0%
M5
 
11.4%
D1
 
2.3%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin166
95.4%
Common8
 
4.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e35
21.1%
s29
17.5%
Y27
16.3%
o18
10.8%
N11
 
6.6%
a7
 
4.2%
y7
 
4.2%
M5
 
3.0%
b5
 
3.0%
n3
 
1.8%
Other values (11)19
11.4%
Common
ValueCountFrequency (%)
7
87.5%
?1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII174
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e35
20.1%
s29
16.7%
Y27
15.5%
o18
10.3%
N11
 
6.3%
a7
 
4.0%
y7
 
4.0%
7
 
4.0%
M5
 
2.9%
b5
 
2.9%
Other values (13)23
13.2%

Is there any luminare is OFF at this moment?
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6
Distinct (%)13.6%
Missing34
Missing (%)43.6%
Memory size752.0 B
No
21 
3
11 
2
4
 
2
How would you describe the ventilation and air quality of building ?
 
1

Length

Max length68
Median length35
Mean length3
Min length1

Characters and Unicode

Total characters132
Distinct characters28
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)4.5%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No21
26.9%
311
 
14.1%
28
 
10.3%
42
 
2.6%
How would you describe the ventilation and air quality of building ?1
 
1.3%
51
 
1.3%
(Missing)34
43.6%

Length

2022-08-24T15:07:05.469235image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:05.619361image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no21
38.2%
311
20.0%
28
 
14.5%
42
 
3.6%
and1
 
1.8%
1
 
1.8%
building1
 
1.8%
of1
 
1.8%
quality1
 
1.8%
air1
 
1.8%
Other values (7)7
 
12.7%

Most occurring characters

ValueCountFrequency (%)
o26
19.7%
N21
15.9%
311
 
8.3%
11
 
8.3%
28
 
6.1%
i7
 
5.3%
d4
 
3.0%
t4
 
3.0%
e4
 
3.0%
a4
 
3.0%
Other values (18)32
24.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter76
57.6%
Uppercase Letter22
 
16.7%
Decimal Number22
 
16.7%
Space Separator11
 
8.3%
Other Punctuation1
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o26
34.2%
i7
 
9.2%
d4
 
5.3%
t4
 
5.3%
e4
 
5.3%
a4
 
5.3%
n4
 
5.3%
l4
 
5.3%
u4
 
5.3%
w2
 
2.6%
Other values (10)13
17.1%
Decimal Number
ValueCountFrequency (%)
311
50.0%
28
36.4%
42
 
9.1%
51
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
N21
95.5%
H1
 
4.5%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin98
74.2%
Common34
 
25.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o26
26.5%
N21
21.4%
i7
 
7.1%
d4
 
4.1%
t4
 
4.1%
e4
 
4.1%
a4
 
4.1%
n4
 
4.1%
l4
 
4.1%
u4
 
4.1%
Other values (12)16
16.3%
Common
ValueCountFrequency (%)
311
32.4%
11
32.4%
28
23.5%
42
 
5.9%
?1
 
2.9%
51
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII132
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o26
19.7%
N21
15.9%
311
 
8.3%
11
 
8.3%
28
 
6.1%
i7
 
5.3%
d4
 
3.0%
t4
 
3.0%
e4
 
3.0%
a4
 
3.0%
Other values (18)32
24.2%

Unnamed: 61
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)17.4%
Missing55
Missing (%)70.5%
Memory size752.0 B
No
16 
Maybe
Yes
Do you smell odor or unusual smell in your work-space?
 
1

Length

Max length54
Median length2
Mean length4.869565217
Min length2

Characters and Unicode

Total characters112
Distinct characters24
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st rowDo you smell odor or unusual smell in your work-space?
2nd rowNo
3rd rowNo
4th rowMaybe
5th rowNo

Common Values

ValueCountFrequency (%)
No16
 
20.5%
Maybe4
 
5.1%
Yes2
 
2.6%
Do you smell odor or unusual smell in your work-space?1
 
1.3%
(Missing)55
70.5%

Length

2022-08-24T15:07:05.755563image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:05.883704image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no16
50.0%
maybe4
 
12.5%
yes2
 
6.2%
smell2
 
6.2%
do1
 
3.1%
you1
 
3.1%
odor1
 
3.1%
or1
 
3.1%
unusual1
 
3.1%
in1
 
3.1%
Other values (2)2
 
6.2%

Most occurring characters

ValueCountFrequency (%)
o23
20.5%
N16
14.3%
e9
 
8.0%
9
 
8.0%
a6
 
5.4%
y6
 
5.4%
s6
 
5.4%
l5
 
4.5%
u5
 
4.5%
M4
 
3.6%
Other values (14)23
20.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter78
69.6%
Uppercase Letter23
 
20.5%
Space Separator9
 
8.0%
Dash Punctuation1
 
0.9%
Other Punctuation1
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o23
29.5%
e9
 
11.5%
a6
 
7.7%
y6
 
7.7%
s6
 
7.7%
l5
 
6.4%
u5
 
6.4%
b4
 
5.1%
r4
 
5.1%
n2
 
2.6%
Other values (7)8
 
10.3%
Uppercase Letter
ValueCountFrequency (%)
N16
69.6%
M4
 
17.4%
Y2
 
8.7%
D1
 
4.3%
Space Separator
ValueCountFrequency (%)
9
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin101
90.2%
Common11
 
9.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o23
22.8%
N16
15.8%
e9
 
8.9%
a6
 
5.9%
y6
 
5.9%
s6
 
5.9%
l5
 
5.0%
u5
 
5.0%
M4
 
4.0%
b4
 
4.0%
Other values (11)17
16.8%
Common
ValueCountFrequency (%)
9
81.8%
-1
 
9.1%
?1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII112
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o23
20.5%
N16
14.3%
e9
 
8.0%
9
 
8.0%
a6
 
5.4%
y6
 
5.4%
s6
 
5.4%
l5
 
4.5%
u5
 
4.5%
M4
 
3.6%
Other values (14)23
20.5%

Unnamed: 62
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)17.4%
Missing55
Missing (%)70.5%
Memory size752.0 B
Yes
10 
No
Maybe
Do you feel sleepy or headache when you get to your work-space?
 
1

Length

Max length63
Median length5
Mean length5.608695652
Min length2

Characters and Unicode

Total characters129
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st rowDo you feel sleepy or headache when you get to your work-space?
2nd rowMaybe
3rd rowMaybe
4th rowNo
5th rowYes

Common Values

ValueCountFrequency (%)
Yes10
 
12.8%
No8
 
10.3%
Maybe4
 
5.1%
Do you feel sleepy or headache when you get to your work-space?1
 
1.3%
(Missing)55
70.5%

Length

2022-08-24T15:07:06.004396image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:06.319328image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
yes10
29.4%
no8
23.5%
maybe4
 
11.8%
you2
 
5.9%
do1
 
2.9%
feel1
 
2.9%
sleepy1
 
2.9%
or1
 
2.9%
headache1
 
2.9%
when1
 
2.9%
Other values (4)4
 
11.8%

Most occurring characters

ValueCountFrequency (%)
e23
17.8%
o15
11.6%
s12
9.3%
11
8.5%
Y10
 
7.8%
N8
 
6.2%
y8
 
6.2%
a7
 
5.4%
M4
 
3.1%
b4
 
3.1%
Other values (16)27
20.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter93
72.1%
Uppercase Letter23
 
17.8%
Space Separator11
 
8.5%
Dash Punctuation1
 
0.8%
Other Punctuation1
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e23
24.7%
o15
16.1%
s12
12.9%
y8
 
8.6%
a7
 
7.5%
b4
 
4.3%
h3
 
3.2%
u3
 
3.2%
r3
 
3.2%
t2
 
2.2%
Other values (9)13
14.0%
Uppercase Letter
ValueCountFrequency (%)
Y10
43.5%
N8
34.8%
M4
 
17.4%
D1
 
4.3%
Space Separator
ValueCountFrequency (%)
11
100.0%
Dash Punctuation
ValueCountFrequency (%)
-1
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin116
89.9%
Common13
 
10.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e23
19.8%
o15
12.9%
s12
10.3%
Y10
8.6%
N8
 
6.9%
y8
 
6.9%
a7
 
6.0%
M4
 
3.4%
b4
 
3.4%
h3
 
2.6%
Other values (13)22
19.0%
Common
ValueCountFrequency (%)
11
84.6%
-1
 
7.7%
?1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII129
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e23
17.8%
o15
11.6%
s12
9.3%
11
8.5%
Y10
 
7.8%
N8
 
6.2%
y8
 
6.2%
a7
 
5.4%
M4
 
3.1%
b4
 
3.1%
Other values (16)27
20.9%

Unnamed: 63
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)17.4%
Missing55
Missing (%)70.5%
Memory size752.0 B
No
11 
Yes
Maybe
Does the quality of light in this part of building have a negative effect on your work performance ?
 
1

Length

Max length100
Median length5
Mean length7.173913043
Min length2

Characters and Unicode

Total characters165
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st rowDoes the quality of light in this part of building have a negative effect on your work performance ?
2nd rowNo
3rd rowYes
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No11
 
14.1%
Yes6
 
7.7%
Maybe5
 
6.4%
Does the quality of light in this part of building have a negative effect on your work performance ?1
 
1.3%
(Missing)55
70.5%

Length

2022-08-24T15:07:06.438657image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:06.565914image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
no11
26.8%
yes6
14.6%
maybe5
12.2%
of2
 
4.9%
have1
 
2.4%
performance1
 
2.4%
work1
 
2.4%
your1
 
2.4%
on1
 
2.4%
effect1
 
2.4%
Other values (11)11
26.8%

Most occurring characters

ValueCountFrequency (%)
e20
 
12.1%
18
 
10.9%
o18
 
10.9%
N11
 
6.7%
a11
 
6.7%
s8
 
4.8%
t7
 
4.2%
i7
 
4.2%
y7
 
4.2%
Y6
 
3.6%
Other values (19)52
31.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter123
74.5%
Uppercase Letter23
 
13.9%
Space Separator18
 
10.9%
Other Punctuation1
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e20
16.3%
o18
14.6%
a11
 
8.9%
s8
 
6.5%
t7
 
5.7%
i7
 
5.7%
y7
 
5.7%
b6
 
4.9%
f5
 
4.1%
r5
 
4.1%
Other values (13)29
23.6%
Uppercase Letter
ValueCountFrequency (%)
N11
47.8%
Y6
26.1%
M5
21.7%
D1
 
4.3%
Space Separator
ValueCountFrequency (%)
18
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin146
88.5%
Common19
 
11.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e20
13.7%
o18
 
12.3%
N11
 
7.5%
a11
 
7.5%
s8
 
5.5%
t7
 
4.8%
i7
 
4.8%
y7
 
4.8%
Y6
 
4.1%
b6
 
4.1%
Other values (17)45
30.8%
Common
ValueCountFrequency (%)
18
94.7%
?1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII165
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e20
 
12.1%
18
 
10.9%
o18
 
10.9%
N11
 
6.7%
a11
 
6.7%
s8
 
4.8%
t7
 
4.2%
i7
 
4.2%
y7
 
4.2%
Y6
 
3.6%
Other values (19)52
31.5%

Unnamed: 64
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct5
Distinct (%)21.7%
Missing55
Missing (%)70.5%
Memory size752.0 B
3
2
1
4
Is there availability of natural light?

Length

Max length39
Median length1
Mean length2.652173913
Min length1

Characters and Unicode

Total characters61
Distinct characters23
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st rowIs there availability of natural light?
2nd row1
3rd row3
4th row3
5th row2

Common Values

ValueCountFrequency (%)
39
 
11.5%
25
 
6.4%
14
 
5.1%
44
 
5.1%
Is there availability of natural light?1
 
1.3%
(Missing)55
70.5%

Length

2022-08-24T15:07:06.693566image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:06.832401image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
39
32.1%
25
17.9%
14
14.3%
44
14.3%
is1
 
3.6%
there1
 
3.6%
availability1
 
3.6%
of1
 
3.6%
natural1
 
3.6%
light1
 
3.6%

Most occurring characters

ValueCountFrequency (%)
39
14.8%
5
 
8.2%
25
 
8.2%
a5
 
8.2%
i4
 
6.6%
44
 
6.6%
t4
 
6.6%
14
 
6.6%
l4
 
6.6%
h2
 
3.3%
Other values (13)15
24.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter32
52.5%
Decimal Number22
36.1%
Space Separator5
 
8.2%
Uppercase Letter1
 
1.6%
Other Punctuation1
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a5
15.6%
i4
12.5%
t4
12.5%
l4
12.5%
h2
 
6.2%
e2
 
6.2%
r2
 
6.2%
o1
 
3.1%
g1
 
3.1%
u1
 
3.1%
Other values (6)6
18.8%
Decimal Number
ValueCountFrequency (%)
39
40.9%
25
22.7%
44
18.2%
14
18.2%
Space Separator
ValueCountFrequency (%)
5
100.0%
Uppercase Letter
ValueCountFrequency (%)
I1
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin33
54.1%
Common28
45.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a5
15.2%
i4
12.1%
t4
12.1%
l4
12.1%
h2
 
6.1%
e2
 
6.1%
r2
 
6.1%
o1
 
3.0%
g1
 
3.0%
u1
 
3.0%
Other values (7)7
21.2%
Common
ValueCountFrequency (%)
39
32.1%
5
17.9%
25
17.9%
44
14.3%
14
14.3%
?1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII61
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
14.8%
5
 
8.2%
25
 
8.2%
a5
 
8.2%
i4
 
6.6%
44
 
6.6%
t4
 
6.6%
14
 
6.6%
l4
 
6.6%
h2
 
3.3%
Other values (13)15
24.6%

Unnamed: 65
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)17.4%
Missing55
Missing (%)70.5%
Memory size752.0 B
Maybe
No
Yes
Are there blinds or shutters blocking the natural light?

Length

Max length56
Median length5
Mean length5.652173913
Min length2

Characters and Unicode

Total characters130
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st rowAre there blinds or shutters blocking the natural light?
2nd rowYes
3rd rowMaybe
4th rowNo
5th rowMaybe

Common Values

ValueCountFrequency (%)
Maybe8
 
10.3%
No8
 
10.3%
Yes6
 
7.7%
Are there blinds or shutters blocking the natural light?1
 
1.3%
(Missing)55
70.5%

Length

2022-08-24T15:07:06.954995image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:07.081956image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
maybe8
25.8%
no8
25.8%
yes6
19.4%
are1
 
3.2%
there1
 
3.2%
blinds1
 
3.2%
or1
 
3.2%
shutters1
 
3.2%
blocking1
 
3.2%
the1
 
3.2%
Other values (2)2
 
6.5%

Most occurring characters

ValueCountFrequency (%)
e19
14.6%
o10
 
7.7%
a10
 
7.7%
b10
 
7.7%
s9
 
6.9%
M8
 
6.2%
8
 
6.2%
N8
 
6.2%
y8
 
6.2%
Y6
 
4.6%
Other values (13)34
26.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter98
75.4%
Uppercase Letter23
 
17.7%
Space Separator8
 
6.2%
Other Punctuation1
 
0.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e19
19.4%
o10
10.2%
a10
10.2%
b10
10.2%
s9
9.2%
y8
8.2%
t6
 
6.1%
r5
 
5.1%
h4
 
4.1%
l4
 
4.1%
Other values (7)13
13.3%
Uppercase Letter
ValueCountFrequency (%)
M8
34.8%
N8
34.8%
Y6
26.1%
A1
 
4.3%
Space Separator
ValueCountFrequency (%)
8
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin121
93.1%
Common9
 
6.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e19
15.7%
o10
 
8.3%
a10
 
8.3%
b10
 
8.3%
s9
 
7.4%
M8
 
6.6%
N8
 
6.6%
y8
 
6.6%
Y6
 
5.0%
t6
 
5.0%
Other values (11)27
22.3%
Common
ValueCountFrequency (%)
8
88.9%
?1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e19
14.6%
o10
 
7.7%
a10
 
7.7%
b10
 
7.7%
s9
 
6.9%
M8
 
6.2%
8
 
6.2%
N8
 
6.2%
y8
 
6.2%
Y6
 
4.6%
Other values (13)34
26.2%

Unnamed: 66
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)17.4%
Missing55
Missing (%)70.5%
Memory size752.0 B
Yes
11 
No
Maybe
Do you have control over artificial lightning?
 
1

Length

Max length46
Median length5
Mean length4.782608696
Min length2

Characters and Unicode

Total characters110
Distinct characters23
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st rowDo you have control over artificial lightning?
2nd rowYes
3rd rowYes
4th rowYes
5th rowMaybe

Common Values

ValueCountFrequency (%)
Yes11
 
14.1%
No8
 
10.3%
Maybe3
 
3.8%
Do you have control over artificial lightning?1
 
1.3%
(Missing)55
70.5%

Length

2022-08-24T15:07:07.197448image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram of lengths of the category

Category Frequency Plot

2022-08-24T15:07:07.321766image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
ValueCountFrequency (%)
yes11
37.9%
no8
27.6%
maybe3
 
10.3%
do1
 
3.4%
you1
 
3.4%
have1
 
3.4%
control1
 
3.4%
over1
 
3.4%
artificial1
 
3.4%
lightning1
 
3.4%

Most occurring characters

ValueCountFrequency (%)
e16
14.5%
o13
11.8%
Y11
10.0%
s11
10.0%
N8
 
7.3%
a6
 
5.5%
6
 
5.5%
i5
 
4.5%
y4
 
3.6%
b3
 
2.7%
Other values (13)27
24.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter80
72.7%
Uppercase Letter23
 
20.9%
Space Separator6
 
5.5%
Other Punctuation1
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e16
20.0%
o13
16.2%
s11
13.8%
a6
 
7.5%
i5
 
6.2%
y4
 
5.0%
b3
 
3.8%
n3
 
3.8%
t3
 
3.8%
r3
 
3.8%
Other values (7)13
16.2%
Uppercase Letter
ValueCountFrequency (%)
Y11
47.8%
N8
34.8%
M3
 
13.0%
D1
 
4.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
?1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin103
93.6%
Common7
 
6.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e16
15.5%
o13
12.6%
Y11
10.7%
s11
10.7%
N8
 
7.8%
a6
 
5.8%
i5
 
4.9%
y4
 
3.9%
b3
 
2.9%
M3
 
2.9%
Other values (11)23
22.3%
Common
ValueCountFrequency (%)
6
85.7%
?1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e16
14.5%
o13
11.8%
Y11
10.0%
s11
10.0%
N8
 
7.3%
a6
 
5.5%
6
 
5.5%
i5
 
4.5%
y4
 
3.6%
b3
 
2.7%
Other values (13)27
24.5%

Correlations

2022-08-24T15:07:07.531597image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-08-24T15:07:09.566436image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-08-24T15:06:45.135463image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-08-24T15:06:47.626984image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2022-08-24T15:06:50.971146image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

LocationTimeDecimalIllumination level (Lux)Color TempretureAverage Noise levelO2 Concentration (%Vol)CO2 at any moment (PPM)LPG concen (ppm)Alcohole Concen (ppm)Methan Concen (ppm)CO concen (ppm)Hydrogyn Concen (ppm)Netric tVOC level (ppm)VOC Formerdahied Level (ppm)Different VOC (CO) Level (ppm)Room Temp ( C )Room reative humadity %Radiant Temp 1 (C)Radiant Temp 2 (C)Radiant Temp 3 (C)Radiant Temp 1 (C).1Wind Speed (mm/s)TimestampRoom name and codeGenderOccupationAgeHeightWeightYour ActivityClothingHow long do you spend in the building during the dayHow long have you (worked-studied) in this buildingIn average day how much time do you spend in the [Office ]In average day how much time do you spend in the [Lecture room ]In average day how much time do you spend in the [laboratory ]In average day how much time do you spend in the [Studio Design]In average day how much time do you spend in the [Cafeteria ]In average day how much time do you spend working at computer "average hours per day"Does the temperature in this part of the building have a negative effect on your work performance?How would you describe the summer indoor air temperature "most time feeling"?How would you describe the winter indoor air temperature "most time feeling"Do you feel comfortable under the current temperature ?How you describe the current temperature in this room?Does the distraction from noise in this part of building have a negative effect on your work performance "most time feeling"?Is there significant distraction from noise outside (in this moment) ?Is there significant distraction from background noise (machine and undefined noise sources)?How would you describe the noise in building generally "most time feeling"?How would describe noise at this moment?Does the quality of air in this part of building have a negative effect on your work performance "most time feeling"?Do you have control over air condition system ?How would you describe the ventilation and air quality of building "most time feeling"?Do you smell odor or unusual smell in your work-space "most time feeling"?Do you feel sleepy or headache when you get to your work-space "most time feeling"?Right now, do you smell unusual smell?Does the quality of light (color and light level) in this part of building have a negative effect on your work performance ?Is there availability of natural light?Are there blinds or shutters blocking the natural light ?Do you have control over artificial lightning ?Is there any luminare is OFF at this moment?Unnamed: 61Unnamed: 62Unnamed: 63Unnamed: 64Unnamed: 65Unnamed: 66
0STU3022:26:26 PMNaN439.16677163.333329.272220.46331280.61123.8860.00430.29845.716742.56530.33240.48553.133125.32551.28332424.66672424.2222132.66674/7/2019 15:19STU302MaleOcc02Age02Hight04Wieg03WalkingDress_364Period_08Stu-Period_01Period_12Period_12Period_01Period_12Period_11Period_12Maybe32Maybe2YesNoYes34NoNo3MaybeNonoNo4YesYesNoNaNNaNNaNNaNNaNNaN
1STU3022:29:07 PMNaN436.96725627.172220.471297.69593.96670.00430.28835.800443.01540.34870.50373.832725.358351.352324.33332524.1111130.33334/7/2019 15:19STU302MaleOcc01Age01Hight05Wieg04WalkingDress_213Period_08Stu-Period_06Period_12Period_01Period_01Period_07Period_01Period_12No33No3NoNoMaybe33NoYes4NoNomaybeYes3NoNoNoNaNNaNNaNNaNNaNNaN
2STU 3022:31:48 PMNaN443.71837272.333328.183320.49671280.97243.84650.00430.29345.800642.42460.26610.47772.965625.241751.466723.666724.33332725133.66674/7/2019 16:55STU302MaleOcc01Age01Hight03Wieg02WalkingDress_364Period_10Stu-Period_03Period_01Period_08Period_11Period_13Period_11Period_08Yes33Maybe2YesMaybeMaybe33YesNo4YesYesnoMaybe2YesYesNoNaNNaNNaNNaNNaNNaN
3STU2072:46:07 PM14.7686240.308636926.423320.6221090.08683.69040.00430.30276.90740.80670.41340.26793.690924.30557.6821232422.6667136.24/7/2019 14:53STU207MaleOcc01Age01Hight04Wieg03WalkingDress_192Period_08Stu-Period_04Period_01Period_12Period_01Period_07Period_11Period_07Yes11No1YesNoNo43NoNo3NoNonoYes3YesYesNoNaNNaNNaNNaNNaNNaN
4STU2072:53:17 PM14.8881190.676010.166729.513920.581070.37333.64210.00420.30116.781540.98720.4150.25993.834824.029259.341719.333320.333322.666720.7778137.54/7/2019 14:59STU207MaleOcc01Age01Hight03Wieg02RunningDress_99Period_10Stu-Period_03Period_11Period_12Period_11Period_12Period_11Period_01Yes13Maybe3YesNoNo22YesNo2NoYesyesNo1YesNoNoNaNNaNNaNNaNNaNNaN
5STU2103:06:43 PM15.1119376.4967683424.911120.4833955.1843.3130.00370.30896.953240.05530.5210.13512.625523.333366.16672321.666725.333323.33331314/7/2019 15:07STU210MaleOcc01Age01Hight04Wieg04WorkingDress_192Period_08Stu-Period_01Period_01Period_12Period_01Period_07Period_11Period_07Yes44Yes2NoNoNo45YesYes5YesYesyesMaybe3YesYesNoNaNNaNNaNNaNNaNNaN
6ELEV40.63152777815.1567154.29256017.558.658320.45960.80373.35960.00370.31187.033840.53560.57010.17653.485223.5566.6752325.52725.1667107.54/7/2019 15:15ELEV4MaleOcc01Age01Hight05Wieg03WalkingDress_220Period_09Stu-Period_03Period_01Period_07Period_01Period_08Period_11Period_13Maybe43No4YesMaybeYes23YesNo4NoMaybenoMaybe3YesYesNoNaNNaNNaNNaNNaNNaN
7STU3043:10:17 PM15.1714563.365794358.566720.32943.83413.17190.00360.2716.415540.02710.43710.13873.478323.6562.45232425241374/7/2019 12:25STU304MaleOcc02Age02Hight03Wieg03WorkingDress_150Period_08Stu-Period_04Period_07Period_12Period_01Period_12Period_01Period_08No23Maybe2YesNoYes34NoNo2NoNonoNo4MaybeYesNoNaNNaNNaNNaNNaNNaN
8STU3043:12:05 PM15.2014463.00756705.536.091720.31941.81623.15490.00350.26746.592640.11190.38810.1332.709223.41256322.522.524231284/7/2019 12:33STU304MaleOcc02Age02Hight04Wieg03WalkingDress_364Period_07Stu-Period_03Period_07Period_11Period_11Period_12Period_01Period_11No32Yes3YesYesNo22YesNo3YesNonoNo1YesYesNoNaNNaNNaNNaNNaNNaN
9STU3043:13:52 PM15.2311383.94257644.553.116720.425921.36163.08690.00360.27476.37240.19670.36530.16363.478323.337560.722.524.525.524.16671354/7/2019 12:41STU304MaleOcc02Age02Hight04Wieg04WorkingDress_364Period_08Stu-Period_02Period_12Period_11Period_11Period_12Period_01Period_12No33Yes3YesNoNo33NoNo2YesNonoNo3YesYesNoNaNNaNNaNNaNNaNNaN

Last rows

LocationTimeDecimalIllumination level (Lux)Color TempretureAverage Noise levelO2 Concentration (%Vol)CO2 at any moment (PPM)LPG concen (ppm)Alcohole Concen (ppm)Methan Concen (ppm)CO concen (ppm)Hydrogyn Concen (ppm)Netric tVOC level (ppm)VOC Formerdahied Level (ppm)Different VOC (CO) Level (ppm)Room Temp ( C )Room reative humadity %Radiant Temp 1 (C)Radiant Temp 2 (C)Radiant Temp 3 (C)Radiant Temp 1 (C).1Wind Speed (mm/s)TimestampRoom name and codeGenderOccupationAgeHeightWeightYour ActivityClothingHow long do you spend in the building during the dayHow long have you (worked-studied) in this buildingIn average day how much time do you spend in the [Office ]In average day how much time do you spend in the [Lecture room ]In average day how much time do you spend in the [laboratory ]In average day how much time do you spend in the [Studio Design]In average day how much time do you spend in the [Cafeteria ]In average day how much time do you spend working at computer "average hours per day"Does the temperature in this part of the building have a negative effect on your work performance?How would you describe the summer indoor air temperature "most time feeling"?How would you describe the winter indoor air temperature "most time feeling"Do you feel comfortable under the current temperature ?How you describe the current temperature in this room?Does the distraction from noise in this part of building have a negative effect on your work performance "most time feeling"?Is there significant distraction from noise outside (in this moment) ?Is there significant distraction from background noise (machine and undefined noise sources)?How would you describe the noise in building generally "most time feeling"?How would describe noise at this moment?Does the quality of air in this part of building have a negative effect on your work performance "most time feeling"?Do you have control over air condition system ?How would you describe the ventilation and air quality of building "most time feeling"?Do you smell odor or unusual smell in your work-space "most time feeling"?Do you feel sleepy or headache when you get to your work-space "most time feeling"?Right now, do you smell unusual smell?Does the quality of light (color and light level) in this part of building have a negative effect on your work performance ?Is there availability of natural light?Are there blinds or shutters blocking the natural light ?Do you have control over artificial lightning ?Is there any luminare is OFF at this moment?Unnamed: 61Unnamed: 62Unnamed: 63Unnamed: 64Unnamed: 65Unnamed: 66
68STU21111:57:22 AM11.9561156.71357116.384633.324420.3308867.49963.45270.00360.35527.583446.33730.68360.66097.427722.686561.292321.538522.307724.615422.8205134.76924/10/2019 11:57STU211MaleOcc01Age01Hight02Wieg05WalkingDress_364Period_0443NoNoYes43LittleWindy3NoNo333yesNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
69STU21112:01:51 PM12.0308117.187145.822.8220.33874.89423.45870.00360.35877.707246.58210.63020.67487.606722.71560.8621.622.224.422.7333135.44/10/2019 12:00STU211MaleOcc01Age01Hight04Wieg01ClimbingStairsDress_213Period_0533NoNoYes23LittleWindy4NoNo443NoNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
70STU21112:15:16 PM12.254452.77637112.533331.458920.3447891.21043.43470.00350.34117.329746.48510.63680.65856.729222.671759.8320.933322.666723.866722.4889135.24/10/2019 12:15STU211MaleOcc01Age01Hight03Wieg01WorkingDress_364Period_0243NoYesYes43LittleWindy4NoYes435yesNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
71STU2111:22:24 PM13.3733205.74477265.333331.005620.3017984.21572.9810.00290.33827.353446.13570.65280.54865.820122.17564.758320.333323.333323.833322.5136.54/10/2019 13:23STU211MaleOcc01Age01Hight04Wieg02WorkingDress_220Period_0322NoNoNo43LittleWindy4NoYes543NoNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
72STU2111:27:46 PM13.4628138.21837249.833340.783320.2917968.69583.01420.0030.33897.463445.95770.69090.50755.67622.283365.31672324.16672423.7222136.83334/10/2019 13:27STU211MaleOcc01Age01Hight04Wieg04WalkingDress_365Period_0343NoNoMaybe53Negligable3NoNo453yesNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
73STU2111:35:50 PM13.5972153.12947272.222229.255620.2778986.63522.91960.00290.32427.463245.85510.72390.52735.77522.266765.005619.888922.777823.111121.92591374/10/2019 13:35STU211MaleOcc01Age01Hight04Wieg05WorkingDress_365Period_0332NoNoYes33LittleWindy3NoNo542yesNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
74STU2111:40:18 PM13.6717325.2487234.426.133320.331016.53152.88980.00280.3237.378845.84430.66890.52225.67322.22564.9422.4232523.46671364/9/2019 13:35STU211MaleOcc02Age02Hight03Wieg05WorkingDress_192Period_0522NoNoYes32Negligable5NoNo555NoNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
75STU2111:44:47 PM13.7464320.871726932.263320.336997.31512.90240.00280.31667.287545.98040.69940.46626.192422.37565.0521.624.82624.1333137.84/10/2019 13:44STU211MaleOcc01Age01Hight05Wieg01RunningDress_220Period_0324NoMaybeNo52LittleWindy3MaybeNo333yesNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
76STU2112:45:38 PM14.7606317.80457178.323534.090420.32341120.2182.76290.00280.28967.09145.4570.63370.47615.865922.31163.1362123.191224.044122.7451137.05884/10/2019 14:45STU211MaleOcc01Age02Hight03Wieg02WalkingDress_365Period_0543NoNoYes25Negligable4NoNo454yesNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
77STU2112:50:07 PM14.835350.6577030.623.6720.3641030.12532.69130.00260.27927.206445.61110.64780.48216.01522.18562.1122.421.822.622.2667136.84/10/2019 16:37STU211MaleOcc02Age03Hight04Wieg05RunningDress_213Period_0544NoNoYes34Negligable4NoNo444yesNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN